i research paper

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I-Search Paper Format Guide

202.448-7036

An I-Search paper is a personal research paper about a topic that is important to the writer. An I-Search paper is usually less formal than a traditional research paper; it tells the story of the writer’s personal search for information, as well as what the writer learned about the topic.

Many I-Search papers use the structure illustrated in this framework:

The Search Story

• Hook readers immediately. Your readers are more likely to care about your topic if you begin with an attention-getting opener. Help them understand why it was important for you to find out more about the topic.
• Explain what you already knew about your topic. Briefly describe your prior knowledge about the topic before you started your research.
• Tell what you wanted to learn and why . Explain why the topic is important to you, and let readers know what motivated your search.
• Include a thesis statement. Turn your research question into a statement that is based on your research.
• Retrace your research steps. Tell readers about your sources – how you found them and why you used them.

The Search Results

Describe the significance of your research experience. Restate your thesis.

Discuss your results and give support . Describe the findings of your research. Write at least one paragraph for each major research result. Support your findings with quotations, paraphrases, and summaries of information from sources.

Search Reflections

Describe important results of your research. Support your findings.

Reflect on your search . Describe what you learned and how your research experience might have changed you and your future. Also, remind readers of your thesis.

Source: This Writer’s Model has been formatted according to the standards of the MLA Handbook for Writers of Research Papers , Fifth Edition | Copyright © by Holt, Rinehart, and Winston. All rights renewed.

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How To Write A Research Paper

Step-By-Step Tutorial With Examples + FREE Template

By: Derek Jansen (MBA) | Expert Reviewer: Dr Eunice Rautenbach | March 2024

For many students, crafting a strong research paper from scratch can feel like a daunting task – and rightly so! In this post, we’ll unpack what a research paper is, what it needs to do , and how to write one – in three easy steps. 🙂 

Overview: Writing A Research Paper

What (exactly) is a research paper.

• How to write a research paper
• Stage 1 : Topic & literature search
• Stage 2 : Structure & outline
• Stage 3 : Iterative writing
• Key takeaways

Let’s start by asking the most important question, “ What is a research paper? ”.

Simply put, a research paper is a scholarly written work where the writer (that’s you!) answers a specific question (this is called a research question ) through evidence-based arguments . Evidence-based is the keyword here. In other words, a research paper is different from an essay or other writing assignments that draw from the writer’s personal opinions or experiences. With a research paper, it’s all about building your arguments based on evidence (we’ll talk more about that evidence a little later).

Now, it’s worth noting that there are many different types of research papers , including analytical papers (the type I just described), argumentative papers, and interpretative papers. Here, we’ll focus on analytical papers , as these are some of the most common – but if you’re keen to learn about other types of research papers, be sure to check out the rest of the blog .

With that basic foundation laid, let’s get down to business and look at how to write a research paper .

Overview: The 3-Stage Process

While there are, of course, many potential approaches you can take to write a research paper, there are typically three stages to the writing process. So, in this tutorial, we’ll present a straightforward three-step process that we use when working with students at Grad Coach.

These three steps are:

• Finding a research topic and reviewing the existing literature
• Developing a provisional structure and outline for your paper, and
• Writing up your initial draft and then refining it iteratively

Let’s dig into each of these.

Need a helping hand?

Step 1: Find a topic and review the literature

As we mentioned earlier, in a research paper, you, as the researcher, will try to answer a question . More specifically, that’s called a research question , and it sets the direction of your entire paper. What’s important to understand though is that you’ll need to answer that research question with the help of high-quality sources – for example, journal articles, government reports, case studies, and so on. We’ll circle back to this in a minute.

The first stage of the research process is deciding on what your research question will be and then reviewing the existing literature (in other words, past studies and papers) to see what they say about that specific research question. In some cases, your professor may provide you with a predetermined research question (or set of questions). However, in many cases, you’ll need to find your own research question within a certain topic area.

Finding a strong research question hinges on identifying a meaningful research gap – in other words, an area that’s lacking in existing research. There’s a lot to unpack here, so if you wanna learn more, check out the plain-language explainer video below.

Once you’ve figured out which question (or questions) you’ll attempt to answer in your research paper, you’ll need to do a deep dive into the existing literature – this is called a “ literature search ”. Again, there are many ways to go about this, but your most likely starting point will be Google Scholar .

If you’re new to Google Scholar, think of it as Google for the academic world. You can start by simply entering a few different keywords that are relevant to your research question and it will then present a host of articles for you to review. What you want to pay close attention to here is the number of citations for each paper – the more citations a paper has, the more credible it is (generally speaking – there are some exceptions, of course).

Ideally, what you’re looking for are well-cited papers that are highly relevant to your topic. That said, keep in mind that citations are a cumulative metric , so older papers will often have more citations than newer papers – just because they’ve been around for longer. So, don’t fixate on this metric in isolation – relevance and recency are also very important.

Beyond Google Scholar, you’ll also definitely want to check out academic databases and aggregators such as Science Direct, PubMed, JStor and so on. These will often overlap with the results that you find in Google Scholar, but they can also reveal some hidden gems – so, be sure to check them out.

Once you’ve worked your way through all the literature, you’ll want to catalogue all this information in some sort of spreadsheet so that you can easily recall who said what, when and within what context. If you’d like, we’ve got a free literature spreadsheet that helps you do exactly that.

Step 2: Develop a structure and outline

With your research question pinned down and your literature digested and catalogued, it’s time to move on to planning your actual research paper .

It might sound obvious, but it’s really important to have some sort of rough outline in place before you start writing your paper. So often, we see students eagerly rushing into the writing phase, only to land up with a disjointed research paper that rambles on in multiple

Now, the secret here is to not get caught up in the fine details . Realistically, all you need at this stage is a bullet-point list that describes (in broad strokes) what you’ll discuss and in what order. It’s also useful to remember that you’re not glued to this outline – in all likelihood, you’ll chop and change some sections once you start writing, and that’s perfectly okay. What’s important is that you have some sort of roadmap in place from the start.

At this stage you might be wondering, “ But how should I structure my research paper? ”. Well, there’s no one-size-fits-all solution here, but in general, a research paper will consist of a few relatively standardised components:

• Introduction
• Literature review
• Methodology

Let’s take a look at each of these.

First up is the introduction section . As the name suggests, the purpose of the introduction is to set the scene for your research paper. There are usually (at least) four ingredients that go into this section – these are the background to the topic, the research problem and resultant research question , and the justification or rationale. If you’re interested, the video below unpacks the introduction section in more detail. 

The next section of your research paper will typically be your literature review . Remember all that literature you worked through earlier? Well, this is where you’ll present your interpretation of all that content . You’ll do this by writing about recent trends, developments, and arguments within the literature – but more specifically, those that are relevant to your research question . The literature review can oftentimes seem a little daunting, even to seasoned researchers, so be sure to check out our extensive collection of literature review content here .

With the introduction and lit review out of the way, the next section of your paper is the research methodology . In a nutshell, the methodology section should describe to your reader what you did (beyond just reviewing the existing literature) to answer your research question. For example, what data did you collect, how did you collect that data, how did you analyse that data and so on? For each choice, you’ll also need to justify why you chose to do it that way, and what the strengths and weaknesses of your approach were.

Now, it’s worth mentioning that for some research papers, this aspect of the project may be a lot simpler . For example, you may only need to draw on secondary sources (in other words, existing data sets). In some cases, you may just be asked to draw your conclusions from the literature search itself (in other words, there may be no data analysis at all). But, if you are required to collect and analyse data, you’ll need to pay a lot of attention to the methodology section. The video below provides an example of what the methodology section might look like.

By this stage of your paper, you will have explained what your research question is, what the existing literature has to say about that question, and how you analysed additional data to try to answer your question. So, the natural next step is to present your analysis of that data . This section is usually called the “results” or “analysis” section and this is where you’ll showcase your findings.

Depending on your school’s requirements, you may need to present and interpret the data in one section – or you might split the presentation and the interpretation into two sections. In the latter case, your “results” section will just describe the data, and the “discussion” is where you’ll interpret that data and explicitly link your analysis back to your research question. If you’re not sure which approach to take, check in with your professor or take a look at past papers to see what the norms are for your programme.

Alright – once you’ve presented and discussed your results, it’s time to wrap it up . This usually takes the form of the “ conclusion ” section. In the conclusion, you’ll need to highlight the key takeaways from your study and close the loop by explicitly answering your research question. Again, the exact requirements here will vary depending on your programme (and you may not even need a conclusion section at all) – so be sure to check with your professor if you’re unsure.

Step 3: Write and refine

Finally, it’s time to get writing. All too often though, students hit a brick wall right about here… So, how do you avoid this happening to you?

Well, there’s a lot to be said when it comes to writing a research paper (or any sort of academic piece), but we’ll share three practical tips to help you get started.

First and foremost , it’s essential to approach your writing as an iterative process. In other words, you need to start with a really messy first draft and then polish it over multiple rounds of editing. Don’t waste your time trying to write a perfect research paper in one go. Instead, take the pressure off yourself by adopting an iterative approach.

Secondly , it’s important to always lean towards critical writing , rather than descriptive writing. What does this mean? Well, at the simplest level, descriptive writing focuses on the “ what ”, while critical writing digs into the “ so what ” – in other words, the implications . If you’re not familiar with these two types of writing, don’t worry! You can find a plain-language explanation here.

Last but not least, you’ll need to get your referencing right. Specifically, you’ll need to provide credible, correctly formatted citations for the statements you make. We see students making referencing mistakes all the time and it costs them dearly. The good news is that you can easily avoid this by using a simple reference manager . If you don’t have one, check out our video about Mendeley, an easy (and free) reference management tool that you can start using today.

Recap: Key Takeaways

We’ve covered a lot of ground here. To recap, the three steps to writing a high-quality research paper are:

• To choose a research question and review the literature
• To plan your paper structure and draft an outline
• To take an iterative approach to writing, focusing on critical writing and strong referencing

Remember, this is just a b ig-picture overview of the research paper development process and there’s a lot more nuance to unpack. So, be sure to grab a copy of our free research paper template to learn more about how to write a research paper.

You Might Also Like:

Can you help me with a full paper template for this Abstract:

Background: Energy and sports drinks have gained popularity among diverse demographic groups, including adolescents, athletes, workers, and college students. While often used interchangeably, these beverages serve distinct purposes, with energy drinks aiming to boost energy and cognitive performance, and sports drinks designed to prevent dehydration and replenish electrolytes and carbohydrates lost during physical exertion.

Objective: To assess the nutritional quality of energy and sports drinks in Egypt.

Material and Methods: A cross-sectional study assessed the nutrient contents, including energy, sugar, electrolytes, vitamins, and caffeine, of sports and energy drinks available in major supermarkets in Cairo, Alexandria, and Giza, Egypt. Data collection involved photographing all relevant product labels and recording nutritional information. Descriptive statistics and appropriate statistical tests were employed to analyze and compare the nutritional values of energy and sports drinks.

Results: The study analyzed 38 sports drinks and 42 energy drinks. Sports drinks were significantly more expensive than energy drinks, with higher net content and elevated magnesium, potassium, and vitamin C. Energy drinks contained higher concentrations of caffeine, sugars, and vitamins B2, B3, and B6.

Conclusion: Significant nutritional differences exist between sports and energy drinks, reflecting their intended uses. However, these beverages’ high sugar content and calorie loads raise health concerns. Proper labeling, public awareness, and responsible marketing are essential to guide safe consumption practices in Egypt.

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How to Write a Research Paper

Use the links below to jump directly to any section of this guide:

Research Paper Fundamentals

How to choose a topic or question, how to create a working hypothesis or thesis, common research paper methodologies, how to gather and organize evidence , how to write an outline for your research paper, how to write a rough draft, how to revise your draft, how to produce a final draft, resources for teachers .

It is not fair to say that no one writes anymore. Just about everyone writes text messages, brief emails, or social media posts every single day. Yet, most people don't have a lot of practice with the formal, organized writing required for a good academic research paper. This guide contains links to a variety of resources that can help demystify the process. Some of these resources are intended for teachers; they contain exercises, activities, and teaching strategies. Other resources are intended for direct use by students who are struggling to write papers, or are looking for tips to make the process go more smoothly.

The resources in this section are designed to help students understand the different types of research papers, the general research process, and how to manage their time. Below, you'll find links from university writing centers, the trusted Purdue Online Writing Lab, and more.

What is an Academic Research Paper?

"Genre and the Research Paper" (Purdue OWL)

There are different types of research papers. Different types of scholarly questions will lend themselves to one format or another. This is a brief introduction to the two main genres of research paper: analytic and argumentative. 

"7 Most Popular Types of Research Papers" (Personal-writer.com)

This resource discusses formats that high school students commonly encounter, such as the compare and contrast essay and the definitional essay. Please note that the inclusion of this link is not an endorsement of this company's paid service.

How to Prepare and Plan Out Writing a Research Paper

Teachers can give their students a step-by-step guide like these to help them understand the different steps of the research paper process. These guides can be combined with the time management tools in the next subsection to help students come up with customized calendars for completing their papers.

"Ten Steps for Writing Research Papers" (American University)  

This resource from American University is a comprehensive guide to the research paper writing process, and includes examples of proper research questions and thesis topics.

"Steps in Writing a Research Paper" (SUNY Empire State College)

This guide breaks the research paper process into 11 steps. Each "step" links to a separate page, which describes the work entailed in completing it.

How to Manage Time Effectively

The links below will help students determine how much time is necessary to complete a paper. If your sources are not available online or at your local library, you'll need to leave extra time for the Interlibrary Loan process. Remember that, even if you do not need to consult secondary sources, you'll still need to leave yourself ample time to organize your thoughts.

"Research Paper Planner: Timeline" (Baylor University)

This interactive resource from Baylor University creates a suggested writing schedule based on how much time a student has to work on the assignment.

"Research Paper Planner" (UCLA)

UCLA's library offers this step-by-step guide to the research paper writing process, which also includes a suggested planning calendar.

There's a reason teachers spend a long time talking about choosing a good topic. Without a good topic and a well-formulated research question, it is almost impossible to write a clear and organized paper. The resources below will help you generate ideas and formulate precise questions.

"How to Select a Research Topic" (Univ. of Michigan-Flint)

This resource is designed for college students who are struggling to come up with an appropriate topic. A student who uses this resource and still feels unsure about his or her topic should consult the course instructor for further personalized assistance.

"25 Interesting Research Paper Topics to Get You Started" (Kibin)

This resource, which is probably most appropriate for high school students, provides a list of specific topics to help get students started. It is broken into subsections, such as "paper topics on local issues."

"Writing a Good Research Question" (Grand Canyon University)

This introduction to research questions includes some embedded videos, as well as links to scholarly articles on research questions. This resource would be most appropriate for teachers who are planning lessons on research paper fundamentals.

"How to Write a Research Question the Right Way" (Kibin)

This student-focused resource provides more detail on writing research questions. The language is accessible, and there are embedded videos and examples of good and bad questions.

It is important to have a rough hypothesis or thesis in mind at the beginning of the research process. People who have a sense of what they want to say will have an easier time sorting through scholarly sources and other information. The key, of course, is not to become too wedded to the draft hypothesis or thesis. Just about every working thesis gets changed during the research process.

CrashCourse Video: "Sociology Research Methods" (YouTube)

Although this video is tailored to sociology students, it is applicable to students in a variety of social science disciplines. This video does a good job demonstrating the connection between the brainstorming that goes into selecting a research question and the formulation of a working hypothesis.

"How to Write a Thesis Statement for an Analytical Essay" (YouTube)

Students writing analytical essays will not develop the same type of working hypothesis as students who are writing research papers in other disciplines. For these students, developing the working thesis may happen as a part of the rough draft (see the relevant section below). 

"Research Hypothesis" (Oakland Univ.)

This resource provides some examples of hypotheses in social science disciplines like Political Science and Criminal Justice. These sample hypotheses may also be useful for students in other soft social sciences and humanities disciplines like History.

When grading a research paper, instructors look for a consistent methodology. This section will help you understand different methodological approaches used in research papers. Students will get the most out of these resources if they use them to help prepare for conversations with teachers or discussions in class.

"Types of Research Designs" (USC)

A "research design," used for complex papers, is related to the paper's method. This resource contains introductions to a variety of popular research designs in the social sciences. Although it is not the most intuitive site to read, the information here is very valuable. 

"Major Research Methods" (YouTube)

Although this video is a bit on the dry side, it provides a comprehensive overview of the major research methodologies in a format that might be more accessible to students who have struggled with textbooks or other written resources.

"Humanities Research Strategies" (USC)

This is a portal where students can learn about four methodological approaches for humanities papers: Historical Methodologies, Textual Criticism, Conceptual Analysis, and the Synoptic method.

"Selected Major Social Science Research Methods: Overview" (National Academies Press)

This appendix from the book  Using Science as Evidence in Public Policy , printed by National Academies Press, introduces some methods used in social science papers.

"Organizing Your Social Sciences Research Paper: 6. The Methodology" (USC)

This resource from the University of Southern California's library contains tips for writing a methodology section in a research paper.

How to Determine the Best Methodology for You

Anyone who is new to writing research papers should be sure to select a method in consultation with their instructor. These resources can be used to help prepare for that discussion. They may also be used on their own by more advanced students.

"Choosing Appropriate Research Methodologies" (Palgrave Study Skills)

This friendly and approachable resource from Palgrave Macmillan can be used by students who are just starting to think about appropriate methodologies.

"How to Choose Your Research Methods" (NFER (UK))

This is another approachable resource students can use to help narrow down the most appropriate methods for their research projects.

The resources in this section introduce the process of gathering scholarly sources and collecting evidence. You'll find a range of material here, from introductory guides to advanced explications best suited to college students. Please consult the LitCharts  How to Do Academic Research guide for a more comprehensive list of resources devoted to finding scholarly literature.

Google Scholar

Students who have access to library websites with detailed research guides should start there, but people who do not have access to those resources can begin their search for secondary literature here.

"Gathering Appropriate Information" (Texas Gateway)

This resource from the Texas Gateway for online resources introduces students to the research process, and contains interactive exercises. The level of complexity is suitable for middle school, high school, and introductory college classrooms.

"An Overview of Quantitative and Qualitative Data Collection Methods" (NSF)

This PDF from the National Science Foundation goes into detail about best practices and pitfalls in data collection across multiple types of methodologies.

"Social Science Methods for Data Collection and Analysis" (Swiss FIT)

This resource is appropriate for advanced undergraduates or teachers looking to create lessons on research design and data collection. It covers techniques for gathering data via interviews, observations, and other methods.

"Collecting Data by In-depth Interviewing" (Leeds Univ.)

This resource contains enough information about conducting interviews to make it useful for teachers who want to create a lesson plan, but is also accessible enough for college juniors or seniors to make use of it on their own.

There is no "one size fits all" outlining technique. Some students might devote all their energy and attention to the outline in order to avoid the paper. Other students may benefit from being made to sit down and organize their thoughts into a lengthy sentence outline. The resources in this section include strategies and templates for multiple types of outlines. 

"Topic vs. Sentence Outlines" (UC Berkeley)

This resource introduces two basic approaches to outlining: the shorter topic-based approach, and the longer, more detailed sentence-based approach. This resource also contains videos on how to develop paper paragraphs from the sentence-based outline.

"Types of Outlines and Samples" (Purdue OWL)

The Purdue Online Writing Lab's guide is a slightly less detailed discussion of different types of outlines. It contains several sample outlines.

"Writing An Outline" (Austin C.C.)

This resource from a community college contains sample outlines from an American history class that students can use as models.

"How to Structure an Outline for a College Paper" (YouTube)

This brief (sub-2 minute) video from the ExpertVillage YouTube channel provides a model of outline writing for students who are struggling with the idea.

"Outlining" (Harvard)

This is a good resource to consult after completing a draft outline. It offers suggestions for making sure your outline avoids things like unnecessary repetition.

As with outlines, rough drafts can take on many different forms. These resources introduce teachers and students to the various approaches to writing a rough draft. This section also includes resources that will help you cite your sources appropriately according to the MLA, Chicago, and APA style manuals.

"Creating a Rough Draft for a Research Paper" (Univ. of Minnesota)

This resource is useful for teachers in particular, as it provides some suggested exercises to help students with writing a basic rough draft. 

Rough Draft Assignment (Duke of Definition)

This sample assignment, with a brief list of tips, was developed by a high school teacher who runs a very successful and well-reviewed page of educational resources.

"Creating the First Draft of Your Research Paper" (Concordia Univ.)

This resource will be helpful for perfectionists or procrastinators, as it opens by discussing the problem of avoiding writing. It also provides a short list of suggestions meant to get students writing.

Using Proper Citations

There is no such thing as a rough draft of a scholarly citation. These links to the three major citation guides will ensure that your citations follow the correct format. Please consult the LitCharts How to Cite Your Sources guide for more resources.

Chicago Manual of Style Citation Guide

Some call  The Chicago Manual of Style , which was first published in 1906, "the editors' Bible." The manual is now in its 17th edition, and is popular in the social sciences, historical journals, and some other fields in the humanities.

APA Citation Guide

According to the American Psychological Association, this guide was developed to aid reading comprehension, clarity of communication, and to reduce bias in language in the social and behavioral sciences. Its first full edition was published in 1952, and it is now in its sixth edition.

MLA Citation Guide

The Modern Language Association style is used most commonly within the liberal arts and humanities. The  MLA Style Manual and Guide to Scholarly Publishing  was first published in 1985 and (as of 2008) is in its third edition.

Any professional scholar will tell you that the best research papers are made in the revision stage. No matter how strong your research question or working thesis, it is not possible to write a truly outstanding paper without devoting energy to revision. These resources provide examples of revision exercises for the classroom, as well as tips for students working independently.

"The Art of Revision" (Univ. of Arizona)

This resource provides a wealth of information and suggestions for both students and teachers. There is a list of suggested exercises that teachers might use in class, along with a revision checklist that is useful for teachers and students alike.

"Script for Workshop on Revision" (Vanderbilt University)

Vanderbilt's guide for leading a 50-minute revision workshop can serve as a model for teachers who wish to guide students through the revision process during classtime. 

"Revising Your Paper" (Univ. of Washington)

This detailed handout was designed for students who are beginning the revision process. It discusses different approaches and methods for revision, and also includes a detailed list of things students should look for while they revise.

"Revising Drafts" (UNC Writing Center)

This resource is designed for students and suggests things to look for during the revision process. It provides steps for the process and has a FAQ for students who have questions about why it is important to revise.

Conferencing with Writing Tutors and Instructors

No writer is so good that he or she can't benefit from meeting with instructors or peer tutors. These resources from university writing, learning, and communication centers provide suggestions for how to get the most out of these one-on-one meetings.

"Getting Feedback" (UNC Writing Center)

This very helpful resource talks about how to ask for feedback during the entire writing process. It contains possible questions that students might ask when developing an outline, during the revision process, and after the final draft has been graded.

"Prepare for Your Tutoring Session" (Otis College of Art and Design)

This guide from a university's student learning center contains a lot of helpful tips for getting the most out of working with a writing tutor.

"The Importance of Asking Your Professor" (Univ. of Waterloo)

This article from the university's Writing and Communication Centre's blog contains some suggestions for how and when to get help from professors and Teaching Assistants.

Once you've revised your first draft, you're well on your way to handing in a polished paper. These resources—each of them produced by writing professionals at colleges and universities—outline the steps required in order to produce a final draft. You'll find proofreading tips and checklists in text and video form.

"Developing a Final Draft of a Research Paper" (Univ. of Minnesota)

While this resource contains suggestions for revision, it also features a couple of helpful checklists for the last stages of completing a final draft.

Basic Final Draft Tips and Checklist (Univ. of Maryland-University College)

This short and accessible resource, part of UMUC's very thorough online guide to writing and research, contains a very basic checklist for students who are getting ready to turn in their final drafts.

Final Draft Checklist (Everett C.C.)

This is another accessible final draft checklist, appropriate for both high school and college students. It suggests reading your essay aloud at least once.

"How to Proofread Your Final Draft" (YouTube)

This video (approximately 5 minutes), produced by Eastern Washington University, gives students tips on proofreading final drafts.

"Proofreading Tips" (Georgia Southern-Armstrong)

This guide will help students learn how to spot common errors in their papers. It suggests focusing on content and editing for grammar and mechanics.

This final set of resources is intended specifically for high school and college instructors. It provides links to unit plans and classroom exercises that can help improve students' research and writing skills. You'll find resources that give an overview of the process, along with activities that focus on how to begin and how to carry out research. 

"Research Paper Complete Resources Pack" (Teachers Pay Teachers)

This packet of assignments, rubrics, and other resources is designed for high school students. The resources in this packet are aligned to Common Core standards.

"Research Paper—Complete Unit" (Teachers Pay Teachers)

This packet of assignments, notes, PowerPoints, and other resources has a 4/4 rating with over 700 ratings. It is designed for high school teachers, but might also be useful to college instructors who work with freshmen.

"Teaching Students to Write Good Papers" (Yale)

This resource from Yale's Center for Teaching and Learning is designed for college instructors, and it includes links to appropriate activities and exercises.

"Research Paper Writing: An Overview" (CUNY Brooklyn)

CUNY Brooklyn offers this complete lesson plan for introducing students to research papers. It includes an accompanying set of PowerPoint slides.

"Lesson Plan: How to Begin Writing a Research Paper" (San Jose State Univ.)

This lesson plan is designed for students in the health sciences, so teachers will have to modify it for their own needs. It includes a breakdown of the brainstorming, topic selection, and research question process. 

"Quantitative Techniques for Social Science Research" (Univ. of Pittsburgh)

This is a set of PowerPoint slides that can be used to introduce students to a variety of quantitative methods used in the social sciences.

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• How to write a research paper

Last updated

11 January 2024

Reviewed by

With proper planning, knowledge, and framework, completing a research paper can be a fulfilling and exciting experience. 

Though it might initially sound slightly intimidating, this guide will help you embrace the challenge. 

By documenting your findings, you can inspire others and make a difference in your field. Here's how you can make your research paper unique and comprehensive.

• What is a research paper?

Research papers allow you to demonstrate your knowledge and understanding of a particular topic. These papers are usually lengthier and more detailed than typical essays, requiring deeper insight into the chosen topic.

To write a research paper, you must first choose a topic that interests you and is relevant to the field of study. Once you’ve selected your topic, gathering as many relevant resources as possible, including books, scholarly articles, credible websites, and other academic materials, is essential. You must then read and analyze these sources, summarizing their key points and identifying gaps in the current research.

You can formulate your ideas and opinions once you thoroughly understand the existing research. To get there might involve conducting original research, gathering data, or analyzing existing data sets. It could also involve presenting an original argument or interpretation of the existing research.

Writing a successful research paper involves presenting your findings clearly and engagingly, which might involve using charts, graphs, or other visual aids to present your data and using concise language to explain your findings. You must also ensure your paper adheres to relevant academic formatting guidelines, including proper citations and references.

Overall, writing a research paper requires a significant amount of time, effort, and attention to detail. However, it is also an enriching experience that allows you to delve deeply into a subject that interests you and contribute to the existing body of knowledge in your chosen field.

• How long should a research paper be?

Research papers are deep dives into a topic. Therefore, they tend to be longer pieces of work than essays or opinion pieces. 

However, a suitable length depends on the complexity of the topic and your level of expertise. For instance, are you a first-year college student or an experienced professional? 

Also, remember that the best research papers provide valuable information for the benefit of others. Therefore, the quality of information matters most, not necessarily the length. Being concise is valuable.

Following these best practice steps will help keep your process simple and productive:

1. Gaining a deep understanding of any expectations

Before diving into your intended topic or beginning the research phase, take some time to orient yourself. Suppose there’s a specific topic assigned to you. In that case, it’s essential to deeply understand the question and organize your planning and approach in response. Pay attention to the key requirements and ensure you align your writing accordingly. 

This preparation step entails

Deeply understanding the task or assignment

Being clear about the expected format and length

Familiarizing yourself with the citation and referencing requirements 

Understanding any defined limits for your research contribution

Where applicable, speaking to your professor or research supervisor for further clarification

2. Choose your research topic

Select a research topic that aligns with both your interests and available resources. Ideally, focus on a field where you possess significant experience and analytical skills. In crafting your research paper, it's crucial to go beyond summarizing existing data and contribute fresh insights to the chosen area.

Consider narrowing your focus to a specific aspect of the topic. For example, if exploring the link between technology and mental health, delve into how social media use during the pandemic impacts the well-being of college students. Conducting interviews and surveys with students could provide firsthand data and unique perspectives, adding substantial value to the existing knowledge.

When finalizing your topic, adhere to legal and ethical norms in the relevant area (this ensures the integrity of your research, protects participants' rights, upholds intellectual property standards, and ensures transparency and accountability). Following these principles not only maintains the credibility of your work but also builds trust within your academic or professional community.

For instance, in writing about medical research, consider legal and ethical norms , including patient confidentiality laws and informed consent requirements. Similarly, if analyzing user data on social media platforms, be mindful of data privacy regulations, ensuring compliance with laws governing personal information collection and use. Aligning with legal and ethical standards not only avoids potential issues but also underscores the responsible conduct of your research.

3. Gather preliminary research

Once you’ve landed on your topic, it’s time to explore it further. You’ll want to discover more about available resources and existing research relevant to your assignment at this stage. 

This exploratory phase is vital as you may discover issues with your original idea or realize you have insufficient resources to explore the topic effectively. This key bit of groundwork allows you to redirect your research topic in a different, more feasible, or more relevant direction if necessary. 

Spending ample time at this stage ensures you gather everything you need, learn as much as you can about the topic, and discover gaps where the topic has yet to be sufficiently covered, offering an opportunity to research it further. 

4. Define your research question

To produce a well-structured and focused paper, it is imperative to formulate a clear and precise research question that will guide your work. Your research question must be informed by the existing literature and tailored to the scope and objectives of your project. By refining your focus, you can produce a thoughtful and engaging paper that effectively communicates your ideas to your readers.

5. Write a thesis statement

A thesis statement is a one-to-two-sentence summary of your research paper's main argument or direction. It serves as an overall guide to summarize the overall intent of the research paper for you and anyone wanting to know more about the research.

A strong thesis statement is:

Concise and clear: Explain your case in simple sentences (avoid covering multiple ideas). It might help to think of this section as an elevator pitch.

Specific: Ensure that there is no ambiguity in your statement and that your summary covers the points argued in the paper.

Debatable: A thesis statement puts forward a specific argument––it is not merely a statement but a debatable point that can be analyzed and discussed.

Here are three thesis statement examples from different disciplines:

Psychology thesis example: "We're studying adults aged 25-40 to see if taking short breaks for mindfulness can help with stress. Our goal is to find practical ways to manage anxiety better."

Environmental science thesis example: "This research paper looks into how having more city parks might make the air cleaner and keep people healthier. I want to find out if more green spaces means breathing fewer carcinogens in big cities."

UX research thesis example: "This study focuses on improving mobile banking for older adults using ethnographic research, eye-tracking analysis, and interactive prototyping. We investigate the usefulness of eye-tracking analysis with older individuals, aiming to spark debate and offer fresh perspectives on UX design and digital inclusivity for the aging population."

6. Conduct in-depth research

A research paper doesn’t just include research that you’ve uncovered from other papers and studies but your fresh insights, too. You will seek to become an expert on your topic––understanding the nuances in the current leading theories. You will analyze existing research and add your thinking and discoveries.  It's crucial to conduct well-designed research that is rigorous, robust, and based on reliable sources. Suppose a research paper lacks evidence or is biased. In that case, it won't benefit the academic community or the general public. Therefore, examining the topic thoroughly and furthering its understanding through high-quality research is essential. That usually means conducting new research. Depending on the area under investigation, you may conduct surveys, interviews, diary studies , or observational research to uncover new insights or bolster current claims.

7. Determine supporting evidence

Not every piece of research you’ve discovered will be relevant to your research paper. It’s important to categorize the most meaningful evidence to include alongside your discoveries. It's important to include evidence that doesn't support your claims to avoid exclusion bias and ensure a fair research paper.

8. Write a research paper outline

Before diving in and writing the whole paper, start with an outline. It will help you to see if more research is needed, and it will provide a framework by which to write a more compelling paper. Your supervisor may even request an outline to approve before beginning to write the first draft of the full paper. An outline will include your topic, thesis statement, key headings, short summaries of the research, and your arguments.

9. Write your first draft

Once you feel confident about your outline and sources, it’s time to write your first draft. While penning a long piece of content can be intimidating, if you’ve laid the groundwork, you will have a structure to help you move steadily through each section. To keep up motivation and inspiration, it’s often best to keep the pace quick. Stopping for long periods can interrupt your flow and make jumping back in harder than writing when things are fresh in your mind.

10. Cite your sources correctly

It's always a good practice to give credit where it's due, and the same goes for citing any works that have influenced your paper. Building your arguments on credible references adds value and authenticity to your research. In the formatting guidelines section, you’ll find an overview of different citation styles (MLA, CMOS, or APA), which will help you meet any publishing or academic requirements and strengthen your paper's credibility. It is essential to follow the guidelines provided by your school or the publication you are submitting to ensure the accuracy and relevance of your citations.

11. Ensure your work is original

It is crucial to ensure the originality of your paper, as plagiarism can lead to serious consequences. To avoid plagiarism, you should use proper paraphrasing and quoting techniques. Paraphrasing is rewriting a text in your own words while maintaining the original meaning. Quoting involves directly citing the source. Giving credit to the original author or source is essential whenever you borrow their ideas or words. You can also use plagiarism detection tools such as Scribbr or Grammarly to check the originality of your paper. These tools compare your draft writing to a vast database of online sources. If you find any accidental plagiarism, you should correct it immediately by rephrasing or citing the source.

12. Revise, edit, and proofread

One of the essential qualities of excellent writers is their ability to understand the importance of editing and proofreading. Even though it's tempting to call it a day once you've finished your writing, editing your work can significantly improve its quality. It's natural to overlook the weaker areas when you've just finished writing a paper. Therefore, it's best to take a break of a day or two, or even up to a week, to refresh your mind. This way, you can return to your work with a new perspective. After some breathing room, you can spot any inconsistencies, spelling and grammar errors, typos, or missing citations and correct them. 

• The best research paper format 

The format of your research paper should align with the requirements set forth by your college, school, or target publication. 

There is no one “best” format, per se. Depending on the stated requirements, you may need to include the following elements:

Title page: The title page of a research paper typically includes the title, author's name, and institutional affiliation and may include additional information such as a course name or instructor's name. 

Table of contents: Include a table of contents to make it easy for readers to find specific sections of your paper.

Abstract: The abstract is a summary of the purpose of the paper.

Methods : In this section, describe the research methods used. This may include collecting data , conducting interviews, or doing field research .

Results: Summarize the conclusions you drew from your research in this section.

Discussion: In this section, discuss the implications of your research . Be sure to mention any significant limitations to your approach and suggest areas for further research.

Tables, charts, and illustrations: Use tables, charts, and illustrations to help convey your research findings and make them easier to understand.

Works cited or reference page: Include a works cited or reference page to give credit to the sources that you used to conduct your research.

Bibliography: Provide a list of all the sources you consulted while conducting your research.

Dedication and acknowledgments : Optionally, you may include a dedication and acknowledgments section to thank individuals who helped you with your research.

• General style and formatting guidelines

Formatting your research paper means you can submit it to your college, journal, or other publications in compliance with their criteria.

Research papers tend to follow the American Psychological Association (APA), Modern Language Association (MLA), or Chicago Manual of Style (CMOS) guidelines.

Here’s how each style guide is typically used:

Chicago Manual of Style (CMOS):

CMOS is a versatile style guide used for various types of writing. It's known for its flexibility and use in the humanities. CMOS provides guidelines for citations, formatting, and overall writing style. It allows for both footnotes and in-text citations, giving writers options based on their preferences or publication requirements.

American Psychological Association (APA):

APA is common in the social sciences. It’s hailed for its clarity and emphasis on precision. It has specific rules for citing sources, creating references, and formatting papers. APA style uses in-text citations with an accompanying reference list. It's designed to convey information efficiently and is widely used in academic and scientific writing.

Modern Language Association (MLA):

MLA is widely used in the humanities, especially literature and language studies. It emphasizes the author-page format for in-text citations and provides guidelines for creating a "Works Cited" page. MLA is known for its focus on the author's name and the literary works cited. It’s frequently used in disciplines that prioritize literary analysis and critical thinking.

To confirm you're using the latest style guide, check the official website or publisher's site for updates, consult academic resources, and verify the guide's publication date. Online platforms and educational resources may also provide summaries and alerts about any revisions or additions to the style guide.

Citing sources

When working on your research paper, it's important to cite the sources you used properly. Your citation style will guide you through this process. Generally, there are three parts to citing sources in your research paper: 

First, provide a brief citation in the body of your essay. This is also known as a parenthetical or in-text citation. 

Second, include a full citation in the Reference list at the end of your paper. Different types of citations include in-text citations, footnotes, and reference lists. 

In-text citations include the author's surname and the date of the citation. 

Footnotes appear at the bottom of each page of your research paper. They may also be summarized within a reference list at the end of the paper. 

A reference list includes all of the research used within the paper at the end of the document. It should include the author, date, paper title, and publisher listed in the order that aligns with your citation style.

10 research paper writing tips:

Following some best practices is essential to writing a research paper that contributes to your field of study and creates a positive impact.

These tactics will help you structure your argument effectively and ensure your work benefits others:

Clear and precise language:  Ensure your language is unambiguous. Use academic language appropriately, but keep it simple. Also, provide clear takeaways for your audience.

Effective idea separation:  Organize the vast amount of information and sources in your paper with paragraphs and titles. Create easily digestible sections for your readers to navigate through.

Compelling intro:  Craft an engaging introduction that captures your reader's interest. Hook your audience and motivate them to continue reading.

Thorough revision and editing:  Take the time to review and edit your paper comprehensively. Use tools like Grammarly to detect and correct small, overlooked errors.

Thesis precision:  Develop a clear and concise thesis statement that guides your paper. Ensure that your thesis aligns with your research's overall purpose and contribution.

Logical flow of ideas:  Maintain a logical progression throughout the paper. Use transitions effectively to connect different sections and maintain coherence.

Critical evaluation of sources:  Evaluate and critically assess the relevance and reliability of your sources. Ensure that your research is based on credible and up-to-date information.

Thematic consistency:  Maintain a consistent theme throughout the paper. Ensure that all sections contribute cohesively to the overall argument.

Relevant supporting evidence:  Provide concise and relevant evidence to support your arguments. Avoid unnecessary details that may distract from the main points.

Embrace counterarguments:  Acknowledge and address opposing views to strengthen your position. Show that you have considered alternative arguments in your field.

7 research tips 

If you want your paper to not only be well-written but also contribute to the progress of human knowledge, consider these tips to take your paper to the next level:

Selecting the appropriate topic: The topic you select should align with your area of expertise, comply with the requirements of your project, and have sufficient resources for a comprehensive investigation.

Use academic databases: Academic databases such as PubMed, Google Scholar, and JSTOR offer a wealth of research papers that can help you discover everything you need to know about your chosen topic.

Critically evaluate sources: It is important not to accept research findings at face value. Instead, it is crucial to critically analyze the information to avoid jumping to conclusions or overlooking important details. A well-written research paper requires a critical analysis with thorough reasoning to support claims.

Diversify your sources: Expand your research horizons by exploring a variety of sources beyond the standard databases. Utilize books, conference proceedings, and interviews to gather diverse perspectives and enrich your understanding of the topic.

Take detailed notes: Detailed note-taking is crucial during research and can help you form the outline and body of your paper.

Stay up on trends: Keep abreast of the latest developments in your field by regularly checking for recent publications. Subscribe to newsletters, follow relevant journals, and attend conferences to stay informed about emerging trends and advancements. 

Engage in peer review: Seek feedback from peers or mentors to ensure the rigor and validity of your research . Peer review helps identify potential weaknesses in your methodology and strengthens the overall credibility of your findings.

• The real-world impact of research papers

Writing a research paper is more than an academic or business exercise. The experience provides an opportunity to explore a subject in-depth, broaden one's understanding, and arrive at meaningful conclusions. With careful planning, dedication, and hard work, writing a research paper can be a fulfilling and enriching experience contributing to advancing knowledge.

How do I publish my research paper? 

Many academics wish to publish their research papers. While challenging, your paper might get traction if it covers new and well-written information. To publish your research paper, find a target publication, thoroughly read their guidelines, format your paper accordingly, and send it to them per their instructions. You may need to include a cover letter, too. After submission, your paper may be peer-reviewed by experts to assess its legitimacy, quality, originality, and methodology. Following review, you will be informed by the publication whether they have accepted or rejected your paper. 

What is a good opening sentence for a research paper? 

Beginning your research paper with a compelling introduction can ensure readers are interested in going further. A relevant quote, a compelling statistic, or a bold argument can start the paper and hook your reader. Remember, though, that the most important aspect of a research paper is the quality of the information––not necessarily your ability to storytell, so ensure anything you write aligns with your goals.

Research paper vs. a research proposal—what’s the difference?

While some may confuse research papers and proposals, they are different documents. 

A research proposal comes before a research paper. It is a detailed document that outlines an intended area of exploration. It includes the research topic, methodology, timeline, sources, and potential conclusions. Research proposals are often required when seeking approval to conduct research. 

A research paper is a summary of research findings. A research paper follows a structured format to present those findings and construct an argument or conclusion.

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What is a research paper?

A research paper is a paper that makes an argument about a topic based on research and analysis.

Any paper requiring the writer to research a particular topic is a research paper. Unlike essays, which are often based largely on opinion and are written from the author's point of view, research papers are based in fact.

A research paper requires you to form an opinion on a topic, research and gain expert knowledge on that topic, and then back up your own opinions and assertions with facts found through your thorough research.

➡️ Read more about  different types of research papers .

What is the difference between a research paper and a thesis?

A thesis is a large paper, or multi-chapter work, based on a topic relating to your field of study.

A thesis is a document students of higher education write to obtain an academic degree or qualification. Usually, it is longer than a research paper and takes multiple years to complete.

Generally associated with graduate/postgraduate studies, it is carried out under the supervision of a professor or other academic of the university.

A major difference between a research paper and a thesis is that:

• a research paper presents certain facts that have already been researched and explained by others
• a thesis starts with a certain scholarly question or statement, which then leads to further research and new findings

This means that a thesis requires the author to input original work and their own findings in a certain field, whereas the research paper can be completed with extensive research only.

➡️ Getting ready to start a research paper or thesis? Take a look at our guides on how to start a research paper or how to come up with a topic for your thesis .

Frequently Asked Questions about research papers

Take a look at this list of the top 21 Free Online Journal and Research Databases , such as ScienceOpen , Directory of Open Access Journals , ERIC , and many more.

Mason Porter, Professor at UCLA, explains in this forum post the main reasons to write a research paper:

• To create new knowledge and disseminate it.
• To teach science and how to write about it in an academic style.
• Some practical benefits: prestige, establishing credentials, requirements for grants or to help one get a future grant proposal, and so on.

Generally, people involved in the academia. Research papers are mostly written by higher education students and professional researchers.

Yes, a research paper is the same as a scientific paper. Both papers have the same purpose and format.

A major difference between a research paper and a thesis is that the former presents certain facts that have already been researched and explained by others, whereas the latter starts with a certain scholarly question or statement, which then leads to further research and new findings.

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Home / Guides / Writing Guides / Paper Types / How to Write a Research Paper

How to Write a Research Paper

Research papers are a requirement for most college courses, so knowing how to write a research paper is important. These in-depth pieces of academic writing can seem pretty daunting, but there’s no need to panic. When broken down into its key components, writing your paper should be a manageable and, dare we say it, enjoyable task.

We’re going to look at the required elements of a paper in detail, and you might also find this webpage to be a  useful reference .

Guide Overview

• What is a research paper?
• How to start a research paper
• Get clear instructions
• Brainstorm ideas
• Choose a topic
• Outline your outline
• Make friends with your librarian
• Find quality sources
• Understand your topic
• A detailed outline
• Keep it factual
• Finalize your thesis statement
• Think about format
• Cite, cite and cite
• The editing process
• Final checks

What is a Research Paper?

A research paper is more than just an extra long essay or encyclopedic regurgitation of facts and figures. The aim of this task is to combine in-depth study of a particular topic with critical thinking and evaluation by the student—that’s you!

There are two main types of research paper: argumentative and analytical.

Argumentative  — takes a stance on a particular topic right from the start, with the aim of persuading the reader of the validity of the argument. These are best suited to topics that are debatable or controversial.

Analytical  — takes no firm stance on a topic initially. Instead it asks a question and should come to an answer through the evaluation of source material. As its name suggests, the aim is to analyze the source material and offer a fresh perspective on the results.

If you wish to further your understanding, you can  learn more here .

A required word count (think thousands!) can make writing that paper seem like an insurmountable task. Don’t worry! Our step-by-step guide will help you write that killer paper with confidence.

How to Start a Research Paper

Don’t rush ahead. Taking care during the planning and preparation stage will save time and hassle later.

Get Clear Instructions

Your lecturer or professor is your biggest ally—after all, they want you to do well. Make sure you get clear guidance from them on both the required format and preferred topics. In some cases, your tutor will assign a topic, or give you a set list to choose from. Often, however, you’ll be expected to select a suitable topic for yourself.

Having a research paper example to look at can also be useful for first-timers, so ask your tutor to supply you with one.

Brainstorm Ideas

Brainstorming research paper ideas is the first step to selecting a topic—and there are various methods you can use to brainstorm, including clustering (also known as mind mapping). Think about the research paper topics that interest you, and identify topics you have a strong opinion on.

Choose a Topic

Once you have a list of potential research paper topics, narrow them down by considering your academic strengths and ‘gaps in the market,’ e.g., don’t choose a common topic that’s been written about many times before. While you want your topic to be fresh and interesting, you also need to ensure there’s enough material available for you to work with. Similarly, while you shouldn’t go for easy research paper topics just for the sake of giving yourself less work, you do need to choose a topic that you feel confident you can do justice to.

Outline Your Outline

It might not be possible to form a full research paper outline until you’ve done some information gathering, but you can think about your overall aim; basically what you want to show and how you’re going to show it. Now’s also a good time to consider your thesis statement, although this might change as you delve into your source material deeper.

Researching the Research

Now it’s time to knuckle down and dig out all the information that’s relevant to your topic. Here are some tips.

Make Friends With Your Librarian

While lots of information gathering can be carried out online from anywhere, there’s still a place for old-fashioned study sessions in the library. A good librarian can help you to locate sources quickly and easily, and might even make suggestions that you hadn’t thought of. They’re great at helping you study and research, but probably can’t save you the best desk by the window.

Find Quality Sources

Not all sources are created equal, so make sure that you’re referring to reputable, reliable information. Examples of sources could include books, magazine articles, scholarly articles, reputable websites, databases and journals. Keywords relating to your topic can help you in your search.

As you search, you should begin to compile a list of references. This will make it much easier later when you are ready to build your paper’s bibliography. Keeping clear notes detailing any sources that you use will help you to avoid accidentally plagiarizing someone else’s work or ideas.

Understand Your Topic

Simply regurgitating facts and figures won’t make for an interesting paper. It’s essential that you fully understand your topic so you can come across as an authority on the subject and present your own ideas on it. You should read around your topic as widely as you can, before narrowing your area of interest for your paper, and critically analyzing your findings.

A Detailed Outline

Once you’ve got a firm grip on your subject and the source material available to you, formulate a detailed outline, including your thesis statement and how you are going to support it. The structure of your paper will depend on the subject type—ask a tutor for a research paper outline example if you’re unsure.

Get Writing!

If you’ve fully understood your topic and gathered quality source materials, bringing it all together should actually be the easy part!

Keep it Factual

There’s no place for sloppy writing in this kind of academic task, so keep your language simple and clear, and your points critical and succinct. The creative part is finding innovative angles and new insights on the topic to make your paper interesting.

Don’t forget about our  verb ,  preposition , and  adverb  pages. You may find useful information to help with your writing!

Finalize Your Thesis Statement

You should now be in a position to finalize your thesis statement, showing clearly what your paper will show, answer or prove. This should usually be a one or two sentence statement; however, it’s the core idea of your paper, and every insight that you include should be relevant to it. Remember, a thesis statement is not merely a summary of your findings. It should present an argument or perspective that the rest of your paper aims to support.

Think About Format

The required style of your research paper format will usually depend on your subject area. For example,  APA format  is normally used for social science subjects, while MLA style is most commonly used for liberal arts and humanities. Still, there are thousands of  more styles . Your tutor should be able to give you clear guidance on how to format your paper, how to structure it, and what elements it should include. Make sure that you follow their instruction. If possible, ask to see a sample research paper in the required format.

Cite, Cite and Cite

As all research paper topics invariably involve referring to other people’s work, it’s vital that you know how to properly cite your sources to avoid unintentional plagiarism. Whether you’re paraphrasing (putting someone else’s ideas into your own words) or directly quoting, the original source needs to be referenced. What style of citation formatting you use will depend on the requirements of your instructor, with common styles including APA and  MLA format , which consist of in-text citations (short citations within the text, enclosed with parentheses) and a reference/works cited list.

The Editing Process

It’s likely that your paper will go through several drafts before you arrive at the very best version. The editing process is your chance to fix any weak points in your paper before submission. You might find that it needs a better balance of both primary and secondary sources (click through to find  more info  on the difference), that an  adjective  could use tweaking, or that you’ve included sources that aren’t relevant or credible. You might even feel that you need to be clearer in your argument, more thorough in your critical analysis, or more balanced in your evaluation.

From a stylistic point of view, you want to ensure that your writing is clear, simple and concise, with no long, rambling sentences or paragraphs. Keeping within the required word count parameters is also important, and another thing to keep in mind is the inclusion of gender-neutral language, to avoid the reinforcement of tired stereotypes.

Don’t forget about our other pages! If you are looking for help with other grammar-related topics, check out our  noun ,  pronoun , and  conjunction  pages.

Final Checks

Once you’re happy with the depth and balance of the arguments and points presented, you can turn your attention to the finer details, such as formatting, spelling, punctuation, grammar and ensuring that your citations are all present and correct. The EasyBib Plus  plagiarism checker  is a handy tool for making sure that your sources are all cited. An EasyBib Plus subscription also comes with access to citation tools that can help you create citations in your choice of format.

Also, double-check your deadline date and the submissions guidelines to avoid any last-minute issues. Take a peek at our other grammar pages while you’re at it. We’ve included numerous links on this page, but we also have an  interjection  page and  determiner  page.

So you’ve done your final checks and handed in your paper according to the submissions guidelines and preferably before deadline day. Congratulations! If your schedule permits, now would be a great time to take a break from your studies. Maybe plan a fun activity with friends or just take the opportunity to rest and relax. A well-earned break from the books will ensure that you return to class refreshed and ready for your next stage of learning—and the next  research paper  requirement your tutor sets!

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Home » Research Paper – Structure, Examples and Writing Guide

Research Paper – Structure, Examples and Writing Guide

Table of Contents

Research Paper

Definition:

Research Paper is a written document that presents the author’s original research, analysis, and interpretation of a specific topic or issue.

It is typically based on Empirical Evidence, and may involve qualitative or quantitative research methods, or a combination of both. The purpose of a research paper is to contribute new knowledge or insights to a particular field of study, and to demonstrate the author’s understanding of the existing literature and theories related to the topic.

Structure of Research Paper

The structure of a research paper typically follows a standard format, consisting of several sections that convey specific information about the research study. The following is a detailed explanation of the structure of a research paper:

The title page contains the title of the paper, the name(s) of the author(s), and the affiliation(s) of the author(s). It also includes the date of submission and possibly, the name of the journal or conference where the paper is to be published.

The abstract is a brief summary of the research paper, typically ranging from 100 to 250 words. It should include the research question, the methods used, the key findings, and the implications of the results. The abstract should be written in a concise and clear manner to allow readers to quickly grasp the essence of the research.

Introduction

The introduction section of a research paper provides background information about the research problem, the research question, and the research objectives. It also outlines the significance of the research, the research gap that it aims to fill, and the approach taken to address the research question. Finally, the introduction section ends with a clear statement of the research hypothesis or research question.

Literature Review

The literature review section of a research paper provides an overview of the existing literature on the topic of study. It includes a critical analysis and synthesis of the literature, highlighting the key concepts, themes, and debates. The literature review should also demonstrate the research gap and how the current study seeks to address it.

The methods section of a research paper describes the research design, the sample selection, the data collection and analysis procedures, and the statistical methods used to analyze the data. This section should provide sufficient detail for other researchers to replicate the study.

The results section presents the findings of the research, using tables, graphs, and figures to illustrate the data. The findings should be presented in a clear and concise manner, with reference to the research question and hypothesis.

The discussion section of a research paper interprets the findings and discusses their implications for the research question, the literature review, and the field of study. It should also address the limitations of the study and suggest future research directions.

The conclusion section summarizes the main findings of the study, restates the research question and hypothesis, and provides a final reflection on the significance of the research.

The references section provides a list of all the sources cited in the paper, following a specific citation style such as APA, MLA or Chicago.

How to Write Research Paper

You can write Research Paper by the following guide:

• Choose a Topic: The first step is to select a topic that interests you and is relevant to your field of study. Brainstorm ideas and narrow down to a research question that is specific and researchable.
• Conduct a Literature Review: The literature review helps you identify the gap in the existing research and provides a basis for your research question. It also helps you to develop a theoretical framework and research hypothesis.
• Develop a Thesis Statement : The thesis statement is the main argument of your research paper. It should be clear, concise and specific to your research question.
• Plan your Research: Develop a research plan that outlines the methods, data sources, and data analysis procedures. This will help you to collect and analyze data effectively.
• Collect and Analyze Data: Collect data using various methods such as surveys, interviews, observations, or experiments. Analyze data using statistical tools or other qualitative methods.
• Organize your Paper : Organize your paper into sections such as Introduction, Literature Review, Methods, Results, Discussion, and Conclusion. Ensure that each section is coherent and follows a logical flow.
• Write your Paper : Start by writing the introduction, followed by the literature review, methods, results, discussion, and conclusion. Ensure that your writing is clear, concise, and follows the required formatting and citation styles.
• Edit and Proofread your Paper: Review your paper for grammar and spelling errors, and ensure that it is well-structured and easy to read. Ask someone else to review your paper to get feedback and suggestions for improvement.
• Cite your Sources: Ensure that you properly cite all sources used in your research paper. This is essential for giving credit to the original authors and avoiding plagiarism.

Research Paper Example

Note : The below example research paper is for illustrative purposes only and is not an actual research paper. Actual research papers may have different structures, contents, and formats depending on the field of study, research question, data collection and analysis methods, and other factors. Students should always consult with their professors or supervisors for specific guidelines and expectations for their research papers.

Research Paper Example sample for Students:

Title: The Impact of Social Media on Mental Health among Young Adults

Abstract: This study aims to investigate the impact of social media use on the mental health of young adults. A literature review was conducted to examine the existing research on the topic. A survey was then administered to 200 university students to collect data on their social media use, mental health status, and perceived impact of social media on their mental health. The results showed that social media use is positively associated with depression, anxiety, and stress. The study also found that social comparison, cyberbullying, and FOMO (Fear of Missing Out) are significant predictors of mental health problems among young adults.

Introduction: Social media has become an integral part of modern life, particularly among young adults. While social media has many benefits, including increased communication and social connectivity, it has also been associated with negative outcomes, such as addiction, cyberbullying, and mental health problems. This study aims to investigate the impact of social media use on the mental health of young adults.

Literature Review: The literature review highlights the existing research on the impact of social media use on mental health. The review shows that social media use is associated with depression, anxiety, stress, and other mental health problems. The review also identifies the factors that contribute to the negative impact of social media, including social comparison, cyberbullying, and FOMO.

Methods : A survey was administered to 200 university students to collect data on their social media use, mental health status, and perceived impact of social media on their mental health. The survey included questions on social media use, mental health status (measured using the DASS-21), and perceived impact of social media on their mental health. Data were analyzed using descriptive statistics and regression analysis.

Results : The results showed that social media use is positively associated with depression, anxiety, and stress. The study also found that social comparison, cyberbullying, and FOMO are significant predictors of mental health problems among young adults.

Discussion : The study’s findings suggest that social media use has a negative impact on the mental health of young adults. The study highlights the need for interventions that address the factors contributing to the negative impact of social media, such as social comparison, cyberbullying, and FOMO.

Conclusion : In conclusion, social media use has a significant impact on the mental health of young adults. The study’s findings underscore the need for interventions that promote healthy social media use and address the negative outcomes associated with social media use. Future research can explore the effectiveness of interventions aimed at reducing the negative impact of social media on mental health. Additionally, longitudinal studies can investigate the long-term effects of social media use on mental health.

Limitations : The study has some limitations, including the use of self-report measures and a cross-sectional design. The use of self-report measures may result in biased responses, and a cross-sectional design limits the ability to establish causality.

Implications: The study’s findings have implications for mental health professionals, educators, and policymakers. Mental health professionals can use the findings to develop interventions that address the negative impact of social media use on mental health. Educators can incorporate social media literacy into their curriculum to promote healthy social media use among young adults. Policymakers can use the findings to develop policies that protect young adults from the negative outcomes associated with social media use.

References :

• Twenge, J. M., & Campbell, W. K. (2019). Associations between screen time and lower psychological well-being among children and adolescents: Evidence from a population-based study. Preventive medicine reports, 15, 100918.
• Primack, B. A., Shensa, A., Escobar-Viera, C. G., Barrett, E. L., Sidani, J. E., Colditz, J. B., … & James, A. E. (2017). Use of multiple social media platforms and symptoms of depression and anxiety: A nationally-representative study among US young adults. Computers in Human Behavior, 69, 1-9.
• Van der Meer, T. G., & Verhoeven, J. W. (2017). Social media and its impact on academic performance of students. Journal of Information Technology Education: Research, 16, 383-398.

Appendix : The survey used in this study is provided below.

Social Media and Mental Health Survey

• How often do you use social media per day?
• Less than 30 minutes
• 30 minutes to 1 hour
• 1 to 2 hours
• 2 to 4 hours
• More than 4 hours
• Which social media platforms do you use?
• Others (Please specify)
• How often do you experience the following on social media?
• Social comparison (comparing yourself to others)
• Cyberbullying
• Fear of Missing Out (FOMO)
• Have you ever experienced any of the following mental health problems in the past month?
• Do you think social media use has a positive or negative impact on your mental health?
• Very positive
• Somewhat positive
• Somewhat negative
• Very negative
• In your opinion, which factors contribute to the negative impact of social media on mental health?
• Social comparison
• In your opinion, what interventions could be effective in reducing the negative impact of social media on mental health?
• Education on healthy social media use
• Counseling for mental health problems caused by social media
• Social media detox programs
• Regulation of social media use

Thank you for your participation!

Applications of Research Paper

Research papers have several applications in various fields, including:

• Advancing knowledge: Research papers contribute to the advancement of knowledge by generating new insights, theories, and findings that can inform future research and practice. They help to answer important questions, clarify existing knowledge, and identify areas that require further investigation.
• Informing policy: Research papers can inform policy decisions by providing evidence-based recommendations for policymakers. They can help to identify gaps in current policies, evaluate the effectiveness of interventions, and inform the development of new policies and regulations.
• Improving practice: Research papers can improve practice by providing evidence-based guidance for professionals in various fields, including medicine, education, business, and psychology. They can inform the development of best practices, guidelines, and standards of care that can improve outcomes for individuals and organizations.
• Educating students : Research papers are often used as teaching tools in universities and colleges to educate students about research methods, data analysis, and academic writing. They help students to develop critical thinking skills, research skills, and communication skills that are essential for success in many careers.
• Fostering collaboration: Research papers can foster collaboration among researchers, practitioners, and policymakers by providing a platform for sharing knowledge and ideas. They can facilitate interdisciplinary collaborations and partnerships that can lead to innovative solutions to complex problems.

When to Write Research Paper

Research papers are typically written when a person has completed a research project or when they have conducted a study and have obtained data or findings that they want to share with the academic or professional community. Research papers are usually written in academic settings, such as universities, but they can also be written in professional settings, such as research organizations, government agencies, or private companies.

Here are some common situations where a person might need to write a research paper:

• For academic purposes: Students in universities and colleges are often required to write research papers as part of their coursework, particularly in the social sciences, natural sciences, and humanities. Writing research papers helps students to develop research skills, critical thinking skills, and academic writing skills.
• For publication: Researchers often write research papers to publish their findings in academic journals or to present their work at academic conferences. Publishing research papers is an important way to disseminate research findings to the academic community and to establish oneself as an expert in a particular field.
• To inform policy or practice : Researchers may write research papers to inform policy decisions or to improve practice in various fields. Research findings can be used to inform the development of policies, guidelines, and best practices that can improve outcomes for individuals and organizations.
• To share new insights or ideas: Researchers may write research papers to share new insights or ideas with the academic or professional community. They may present new theories, propose new research methods, or challenge existing paradigms in their field.

Purpose of Research Paper

The purpose of a research paper is to present the results of a study or investigation in a clear, concise, and structured manner. Research papers are written to communicate new knowledge, ideas, or findings to a specific audience, such as researchers, scholars, practitioners, or policymakers. The primary purposes of a research paper are:

• To contribute to the body of knowledge : Research papers aim to add new knowledge or insights to a particular field or discipline. They do this by reporting the results of empirical studies, reviewing and synthesizing existing literature, proposing new theories, or providing new perspectives on a topic.
• To inform or persuade: Research papers are written to inform or persuade the reader about a particular issue, topic, or phenomenon. They present evidence and arguments to support their claims and seek to persuade the reader of the validity of their findings or recommendations.
• To advance the field: Research papers seek to advance the field or discipline by identifying gaps in knowledge, proposing new research questions or approaches, or challenging existing assumptions or paradigms. They aim to contribute to ongoing debates and discussions within a field and to stimulate further research and inquiry.
• To demonstrate research skills: Research papers demonstrate the author’s research skills, including their ability to design and conduct a study, collect and analyze data, and interpret and communicate findings. They also demonstrate the author’s ability to critically evaluate existing literature, synthesize information from multiple sources, and write in a clear and structured manner.

Characteristics of Research Paper

Research papers have several characteristics that distinguish them from other forms of academic or professional writing. Here are some common characteristics of research papers:

• Evidence-based: Research papers are based on empirical evidence, which is collected through rigorous research methods such as experiments, surveys, observations, or interviews. They rely on objective data and facts to support their claims and conclusions.
• Structured and organized: Research papers have a clear and logical structure, with sections such as introduction, literature review, methods, results, discussion, and conclusion. They are organized in a way that helps the reader to follow the argument and understand the findings.
• Formal and objective: Research papers are written in a formal and objective tone, with an emphasis on clarity, precision, and accuracy. They avoid subjective language or personal opinions and instead rely on objective data and analysis to support their arguments.
• Citations and references: Research papers include citations and references to acknowledge the sources of information and ideas used in the paper. They use a specific citation style, such as APA, MLA, or Chicago, to ensure consistency and accuracy.
• Peer-reviewed: Research papers are often peer-reviewed, which means they are evaluated by other experts in the field before they are published. Peer-review ensures that the research is of high quality, meets ethical standards, and contributes to the advancement of knowledge in the field.
• Objective and unbiased: Research papers strive to be objective and unbiased in their presentation of the findings. They avoid personal biases or preconceptions and instead rely on the data and analysis to draw conclusions.

Advantages of Research Paper

Research papers have many advantages, both for the individual researcher and for the broader academic and professional community. Here are some advantages of research papers:

• Contribution to knowledge: Research papers contribute to the body of knowledge in a particular field or discipline. They add new information, insights, and perspectives to existing literature and help advance the understanding of a particular phenomenon or issue.
• Opportunity for intellectual growth: Research papers provide an opportunity for intellectual growth for the researcher. They require critical thinking, problem-solving, and creativity, which can help develop the researcher’s skills and knowledge.
• Career advancement: Research papers can help advance the researcher’s career by demonstrating their expertise and contributions to the field. They can also lead to new research opportunities, collaborations, and funding.
• Academic recognition: Research papers can lead to academic recognition in the form of awards, grants, or invitations to speak at conferences or events. They can also contribute to the researcher’s reputation and standing in the field.
• Impact on policy and practice: Research papers can have a significant impact on policy and practice. They can inform policy decisions, guide practice, and lead to changes in laws, regulations, or procedures.
• Advancement of society: Research papers can contribute to the advancement of society by addressing important issues, identifying solutions to problems, and promoting social justice and equality.

Limitations of Research Paper

Research papers also have some limitations that should be considered when interpreting their findings or implications. Here are some common limitations of research papers:

• Limited generalizability: Research findings may not be generalizable to other populations, settings, or contexts. Studies often use specific samples or conditions that may not reflect the broader population or real-world situations.
• Potential for bias : Research papers may be biased due to factors such as sample selection, measurement errors, or researcher biases. It is important to evaluate the quality of the research design and methods used to ensure that the findings are valid and reliable.
• Ethical concerns: Research papers may raise ethical concerns, such as the use of vulnerable populations or invasive procedures. Researchers must adhere to ethical guidelines and obtain informed consent from participants to ensure that the research is conducted in a responsible and respectful manner.
• Limitations of methodology: Research papers may be limited by the methodology used to collect and analyze data. For example, certain research methods may not capture the complexity or nuance of a particular phenomenon, or may not be appropriate for certain research questions.
• Publication bias: Research papers may be subject to publication bias, where positive or significant findings are more likely to be published than negative or non-significant findings. This can skew the overall findings of a particular area of research.
• Time and resource constraints: Research papers may be limited by time and resource constraints, which can affect the quality and scope of the research. Researchers may not have access to certain data or resources, or may be unable to conduct long-term studies due to practical limitations.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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About this Strategy Guide

The sense of curiosity behind research writing gets lost in some school-based assignments.  This Strategy Guide provides the foundation for cultivating interest and authority through I-Search writing, including publishing online.

Research Basis

Strategy in practice, related resources.

The cognitive demands of research writing are numerous and daunting.  Selecting, reading, and taking notes from sources; organizing and writing up findings; paying attention to citation and formatting rules.  Students can easily lose sight of the purpose of research as it is conducted in “the real world”—finding the answer to an important question.

The I-Search (Macrorie, 1998) empowers students by making their self-selected questions about themselves, their lives, and their world the focus of the research and writing process.  The strong focus on metacognition—paying attention to and writing about the research process methods and extensive reflection on the importance of the topic and findings—makes for meaningful and purposeful writing.

Online publication resources such as blogging software make for easy production of multimodal, digital writing that can be shared with any number of audiences.

Assaf, L., Ash, G., Saunders, J. and Johnson, J.  (2011).  " Renewing Two Seminal Literacy Practices: I-Charts and I-Search Papers ."  English Journal , 18(4), 31-42.

Lyman, H.  (2006).  “ I-Search in the Age of Information .”  English Journal , 95(4), 62-67.

Macrorie, K. (1998).  The I-Search Paper: Revised Edition of Searching Writing .  Portsmouth, NH: Heinemann-Boynton/Cook.

• Before introducing the I-Search paper, set clear goals and boundaries for the assignment.  In some contexts, a completely open assignment can be successful.  In others, a more limited focus such as research on potential careers (e.g., Lyman, 2006)  may be appropriate.
• Introduce the concept of the I-Search by sharing with students that they will be learning about something that is personally interesting and significant for them—something they have the desire to understand more about.  Have students generate a list of potential topics.
• Review student topic lists and offer supportive feedback—either through written comments or in individual conferences—on the topics that have the most potential for success given the scope of the assignment and the research resources to which students will have access.
• After offering feedback, have students choose the topic that seems to have the most potential and allow them to brainstorm as many questions as they can think of.  When students have had plenty of time to ponder the topic, ask them to choose a tentative central question—the main focus for their inquiry—and four possible sub-questions—questions that will help them narrow their research in support of their main question.  Use the I-Search Chart to help students begin to see the relationships among their inquiry questions.
• Begin the reflective component of the I-Search right away and use the I-Search Chart to help students  write about why they chose the topic they did, what they already know about the topic, and what they hope to learn from their research.  Students will be please to hear at this point that they have already completed a significant section of their first draft.
• Engage reader’s attention and interest; explain why learning more about this topic was personally important for you.
• Explain what you already knew about the topic before you even started researching.
• Let readers know what you wanted to learn and why.  State your main question and the subquestions that support it.
• Retrace your research steps by describing the search terms and sources you used.  Discuss things that went well and things that were challenging.
• Share with readers the “big picture” of your most significant findings.
• Describe your results and give support.
• Use findings statements to orient the reader and develop your ideas with direct quotations, paraphrases, and summaries of information from your sources.
• Properly cite all information from sources.
• Discuss what you learned from your research experience.  How might your experience and what you learned affect your choices or opportunities in the future.
• At this point, the research process might be similar to that of a typical research project except students should have time during every class period to write about their process, questions they’re facing, challenges they’ve overcome, and changes they’ve made to their research process.  Students will not necessarily be able to look ahead to the value of these reflections, so take the time early in the process to model what reflection might look like and offer feedback on their early responses.  You may wish to use the I-Search Process Reflection Chart to help students think through their reflections at various stages of the process.
• Support students as they engage in the research and writing process, offering guidance on potential local contacts for interviews and other sources that can heighten their engagement in the authenticity of the research process.
• To encourage effective organization and synthesis of information from multiple sources, you may wish to have students assign a letter to each of their questions (A through E, for example) and a number to each of their sources (1 through 6, for example).  As they find content that relates to one of their questions, they can write the corresponding letter in the margin.  During drafting, students can use the source numbers as basic citation before incorporating more sophisticated, conventional citation.

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This tool allows students to create an online K-W-L chart. Saving capability makes it easy for them to start the chart before reading and then return to it to reflect on what they learned.

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How to Write a Research Paper

Last Updated: February 18, 2024 Fact Checked

This article was co-authored by Chris Hadley, PhD . Chris Hadley, PhD is part of the wikiHow team and works on content strategy and data and analytics. Chris Hadley earned his PhD in Cognitive Psychology from UCLA in 2006. Chris' academic research has been published in numerous scientific journals. There are 14 references cited in this article, which can be found at the bottom of the page. This article has been fact-checked, ensuring the accuracy of any cited facts and confirming the authority of its sources. This article has been viewed 4,189,391 times.

Whether you’re in a history, literature, or science class, you’ll probably have to write a research paper at some point. It may seem daunting when you’re just starting out, but staying organized and budgeting your time can make the process a breeze. Research your topic, find reliable sources, and come up with a working thesis. Then create an outline and start drafting your paper. Be sure to leave plenty of time to make revisions, as editing is essential if you want to hand in your best work!

Sample Research Papers and Outlines

Researching Your Topic

• For instance, you might start with a general subject, like British decorative arts. Then, as you read, you home in on transferware and pottery. Ultimately, you focus on 1 potter in the 1780s who invented a way to mass-produce patterned tableware.

Tip: If you need to analyze a piece of literature, your task is to pull the work apart into literary elements and explain how the author uses those parts to make their point.

• Authoritative, credible sources include scholarly articles (especially those other authors reference), government websites, scientific studies, and reputable news bureaus. Additionally, check your sources' dates, and make sure the information you gather is up to date.
• Evaluate how other scholars have approached your topic. Identify authoritative sources or works that are accepted as the most important accounts of the subject matter. Additionally, look for debates among scholars, and ask yourself who presents the strongest evidence for their case. [3] X Trustworthy Source Purdue Online Writing Lab Trusted resource for writing and citation guidelines Go to source
• You’ll most likely need to include a bibliography or works cited page, so keep your sources organized. List your sources, format them according to your assigned style guide (such as MLA or Chicago ), and write 2 or 3 summary sentences below each one. [4] X Research source

• Imagine you’re a lawyer in a trial and are presenting a case to a jury. Think of your readers as the jurors; your opening statement is your thesis and you’ll present evidence to the jury to make your case.
• A thesis should be specific rather than vague, such as: “Josiah Spode’s improved formula for bone china enabled the mass production of transfer-printed wares, which expanded the global market for British pottery.”

Drafting Your Essay

• Your outline is your paper’s skeleton. After making the outline, all you’ll need to do is fill in the details.
• For easy reference, include your sources where they fit into your outline, like this: III. Spode vs. Wedgewood on Mass Production A. Spode: Perfected chemical formula with aims for fast production and distribution (Travis, 2002, 43) B. Wedgewood: Courted high-priced luxury market; lower emphasis on mass production (Himmelweit, 2001, 71) C. Therefore: Wedgewood, unlike Spode, delayed the expansion of the pottery market.

• For instance, your opening line could be, “Overlooked in the present, manufacturers of British pottery in the eighteenth and nineteenth centuries played crucial roles in England’s Industrial Revolution.”
• After presenting your thesis, lay out your evidence, like this: “An examination of Spode’s innovative production and distribution techniques will demonstrate the importance of his contributions to the industry and Industrial Revolution at large.”

Tip: Some people prefer to write the introduction first and use it to structure the rest of the paper. However, others like to write the body, then fill in the introduction. Do whichever seems natural to you. If you write the intro first, keep in mind you can tweak it later to reflect your finished paper’s layout.

• After setting the context, you'd include a section on Josiah Spode’s company and what he did to make pottery easier to manufacture and distribute.
• Next, discuss how targeting middle class consumers increased demand and expanded the pottery industry globally.
• Then, you could explain how Spode differed from competitors like Wedgewood, who continued to court aristocratic consumers instead of expanding the market to the middle class.
• The right number of sections or paragraphs depends on your assignment. In general, shoot for 3 to 5, but check your prompt for your assigned length.

• If you bring up a counterargument, make sure it’s a strong claim that’s worth entertaining instead of ones that's weak and easily dismissed.
• Suppose, for instance, you’re arguing for the benefits of adding fluoride to toothpaste and city water. You could bring up a study that suggested fluoride produced harmful health effects, then explain how its testing methods were flawed.

• Sum up your argument, but don’t simply rewrite your introduction using slightly different wording. To make your conclusion more memorable, you could also connect your thesis to a broader topic or theme to make it more relatable to your reader.
• For example, if you’ve discussed the role of nationalism in World War I, you could conclude by mentioning nationalism’s reemergence in contemporary foreign affairs.

Revising Your Paper

• This is also a great opportunity to make sure your paper fulfills the parameters of the assignment and answers the prompt!
• It’s a good idea to put your essay aside for a few hours (or overnight, if you have time). That way, you can start editing it with fresh eyes.

Tip: Try to give yourself at least 2 or 3 days to revise your paper. It may be tempting to simply give your paper a quick read and use the spell-checker to make edits. However, revising your paper properly is more in-depth.

• The passive voice, such as “The door was opened by me,” feels hesitant and wordy. On the other hand, the active voice, or “I opened the door,” feels strong and concise.
• Each word in your paper should do a specific job. Try to avoid including extra words just to fill up blank space on a page or sound fancy.
• For instance, “The author uses pathos to appeal to readers’ emotions” is better than “The author utilizes pathos to make an appeal to the emotional core of those who read the passage.”

• Read your essay out loud to help ensure you catch every error. As you read, check for flow as well and, if necessary, tweak any spots that sound awkward. [13] X Trustworthy Source University of North Carolina Writing Center UNC's on-campus and online instructional service that provides assistance to students, faculty, and others during the writing process Go to source

• It’s wise to get feedback from one person who’s familiar with your topic and another who’s not. The person who knows about the topic can help ensure you’ve nailed all the details. The person who’s unfamiliar with the topic can help make sure your writing is clear and easy to understand.

Community Q&A

• Remember that your topic and thesis should be as specific as possible. Thanks Helpful 5 Not Helpful 0
• Researching, outlining, drafting, and revising are all important steps, so do your best to budget your time wisely. Try to avoid waiting until the last minute to write your paper. Thanks Helpful 6 Not Helpful 2

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• ↑ https://writing.wisc.edu/handbook/assignments/planresearchpaper/
• ↑ https://writingcenter.unc.edu/tips-and-tools/evaluating-print-sources/
• ↑ https://owl.purdue.edu/owl/research_and_citation/conducting_research/research_overview/index.html
• ↑ https://poorvucenter.yale.edu/writing/graduate-writing-lab/writing-through-graduate-school/working-sources
• ↑ https://opentextbc.ca/writingforsuccess/chapter/chapter-5-putting-the-pieces-together-with-a-thesis-statement/
• ↑ https://owl.purdue.edu/owl/general_writing/the_writing_process/developing_an_outline/index.html
• ↑ https://writingcenter.unc.edu/tips-and-tools/introductions/
• ↑ https://academicguides.waldenu.edu/writingcenter/writingprocess/counterarguments
• ↑ https://writingcenter.fas.harvard.edu/pages/ending-essay-conclusions
• ↑ https://writingcenter.unc.edu/tips-and-tools/revising-drafts/
• ↑ https://academicguides.waldenu.edu/formandstyle/writing/scholarlyvoice/activepassive
• ↑ https://writingcenter.unc.edu/tips-and-tools/editing-and-proofreading/
• ↑ https://writingcenter.unc.edu/tips-and-tools/reading-aloud/
• ↑ https://owl.purdue.edu/owl/general_writing/the_writing_process/proofreading/index.html

About This Article

To write a research paper, start by researching your topic at the library, online, or using an academic database. As you conduct your research and take notes, zero in on a specific topic that you want to write about and create a 1-2 sentence thesis to state the focus of your paper. Then, create an outline that includes an introduction, 3 to 5 body paragraphs to present your arguments, and a conclusion to sum up your main points. Once you have your paper's structure organized, draft your paragraphs, focusing on 1 argument per paragraph. Use the information you found through your research to back up your claims and prove your thesis statement. Finally, proofread and revise your content until it's polished and ready to submit. For more information on researching and citing sources, read on! Did this summary help you? Yes No

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Writing a Research Paper

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The Research Paper

There will come a time in most students' careers when they are assigned a research paper. Such an assignment often creates a great deal of unneeded anxiety in the student, which may result in procrastination and a feeling of confusion and inadequacy. This anxiety frequently stems from the fact that many students are unfamiliar and inexperienced with this genre of writing. Never fear—inexperience and unfamiliarity are situations you can change through practice! Writing a research paper is an essential aspect of academics and should not be avoided on account of one's anxiety. In fact, the process of writing a research paper can be one of the more rewarding experiences one may encounter in academics. What is more, many students will continue to do research throughout their careers, which is one of the reasons this topic is so important.

Becoming an experienced researcher and writer in any field or discipline takes a great deal of practice. There are few individuals for whom this process comes naturally. Remember, even the most seasoned academic veterans have had to learn how to write a research paper at some point in their career. Therefore, with diligence, organization, practice, a willingness to learn (and to make mistakes!), and, perhaps most important of all, patience, students will find that they can achieve great things through their research and writing.

The pages in this section cover the following topic areas related to the process of writing a research paper:

• Genre - This section will provide an overview for understanding the difference between an analytical and argumentative research paper.
• Choosing a Topic - This section will guide the student through the process of choosing topics, whether the topic be one that is assigned or one that the student chooses themselves.
• Identifying an Audience - This section will help the student understand the often times confusing topic of audience by offering some basic guidelines for the process.
• Where Do I Begin - This section concludes the handout by offering several links to resources at Purdue, and also provides an overview of the final stages of writing a research paper.

Research Paper Examples

Research paper examples are of great value for students who want to complete their assignments timely and efficiently. If you are a student in the university, your first stop in the quest for research paper examples will be the campus library where you can get to view the research sample papers of lecturers and other professionals in diverse fields plus those of fellow students who preceded you in the campus. Many college departments maintain libraries of previous student work, including large research papers, which current students can examine.

Embark on a journey of academic excellence with iResearchNet, your premier destination for research paper examples that illuminate the path to scholarly success. In the realm of academia, where the pursuit of knowledge is both a challenge and a privilege, the significance of having access to high-quality research paper examples cannot be overstated. These exemplars are not merely papers; they are beacons of insight, guiding students and scholars through the complex maze of academic writing and research methodologies.

At iResearchNet, we understand that the foundation of academic achievement lies in the quality of resources at one’s disposal. This is why we are dedicated to offering a comprehensive collection of research paper examples across a multitude of disciplines. Each example stands as a testament to rigorous research, clear writing, and the deep understanding necessary to advance in one’s academic and professional journey.

Access to superior research paper examples equips learners with the tools to develop their own ideas, arguments, and hypotheses, fostering a cycle of learning and discovery that transcends traditional boundaries. It is with this vision that iResearchNet commits to empowering students and researchers, providing them with the resources to not only meet but exceed the highest standards of academic excellence. Join us on this journey, and let iResearchNet be your guide to unlocking the full potential of your academic endeavors.

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Importance of Research Paper Examples

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A Sample Research Paper on Child Abuse

A research paper represents the pinnacle of academic investigation, a scholarly manuscript that encapsulates a detailed study, analysis, or argument based on extensive independent research. It is an embodiment of the researcher’s ability to synthesize a wealth of information, draw insightful conclusions, and contribute novel perspectives to the existing body of knowledge within a specific field. At its core, a research paper strives to push the boundaries of what is known, challenging existing theories and proposing new insights that could potentially reshape the understanding of a particular subject area.

The objective of writing a research paper is manifold, serving both educational and intellectual pursuits. Primarily, it aims to educate the author, providing a rigorous framework through which they engage deeply with a topic, hone their research and analytical skills, and learn the art of academic writing. Beyond personal growth, the research paper serves the broader academic community by contributing to the collective pool of knowledge, offering fresh perspectives, and stimulating further research. It is a medium through which scholars communicate ideas, findings, and theories, thereby fostering an ongoing dialogue that propels the advancement of science, humanities, and other fields of study.

Research papers can be categorized into various types, each with distinct objectives and methodologies. The most common types include:

• Analytical Research Paper: This type focuses on analyzing different viewpoints represented in the scholarly literature or data. The author critically evaluates and interprets the information, aiming to provide a comprehensive understanding of the topic.
• Argumentative or Persuasive Research Paper: Here, the author adopts a stance on a contentious issue and argues in favor of their position. The objective is to persuade the reader through evidence and logic that the author’s viewpoint is valid or preferable.
• Experimental Research Paper: Often used in the sciences, this type documents the process, results, and implications of an experiment conducted by the author. It provides a detailed account of the methodology, data collected, analysis performed, and conclusions drawn.
• Survey Research Paper: This involves collecting data from a set of respondents about their opinions, behaviors, or characteristics. The paper analyzes this data to draw conclusions about the population from which the sample was drawn.
• Comparative Research Paper: This type involves comparing and contrasting different theories, policies, or phenomena. The aim is to highlight similarities and differences, thereby gaining a deeper understanding of the subjects under review.
• Cause and Effect Research Paper: It explores the reasons behind specific actions, events, or conditions and the consequences that follow. The goal is to establish a causal relationship between variables.
• Review Research Paper: This paper synthesizes existing research on a particular topic, offering a comprehensive analysis of the literature to identify trends, gaps, and consensus in the field.

Understanding the nuances and objectives of these various types of research papers is crucial for scholars and students alike, as it guides their approach to conducting and writing up their research. Each type demands a unique set of skills and perspectives, pushing the author to think critically and creatively about their subject matter. As the academic landscape continues to evolve, the research paper remains a fundamental tool for disseminating knowledge, encouraging innovation, and fostering a culture of inquiry and exploration.

Browse Sample Research Papers

iResearchNet prides itself on offering a wide array of research paper examples across various disciplines, meticulously curated to support students, educators, and researchers in their academic endeavors. Each example embodies the hallmarks of scholarly excellence—rigorous research, analytical depth, and clear, precise writing. Below, we explore the diverse range of research paper examples available through iResearchNet, designed to inspire and guide users in their quest for academic achievement.

Anthropology Research Paper Examples

Our anthropology research paper examples delve into the study of humanity, exploring cultural, social, biological, and linguistic variations among human populations. These papers offer insights into human behavior, traditions, and evolution, providing a comprehensive overview of anthropological research methods and theories.

• Archaeology Research Paper
• Forensic Anthropology Research Paper
• Linguistics Research Paper
• Medical Anthropology Research Paper
• Social Problems Research Paper

Art Research Paper Examples

The art research paper examples feature analyses of artistic expressions across different cultures and historical periods. These papers cover a variety of topics, including art history, criticism, and theory, as well as the examination of specific artworks or movements.

• Performing Arts Research Paper
• Music Research Paper
• Architecture Research Paper
• Theater Research Paper
• Visual Arts Research Paper

Cancer Research Paper Examples

Our cancer research paper examples focus on the latest findings in the field of oncology, discussing the biological mechanisms of cancer, advancements in diagnostic techniques, and innovative treatment strategies. These papers aim to contribute to the ongoing battle against cancer by sharing cutting-edge research.

• Breast Cancer Research Paper
• Leukemia Research Paper
• Lung Cancer Research Paper
• Ovarian Cancer Research Paper
• Prostate Cancer Research Paper

Communication Research Paper Examples

These examples explore the complexities of human communication, covering topics such as media studies, interpersonal communication, and public relations. The papers examine how communication processes affect individuals, societies, and cultures.

• Advertising Research Paper
• Journalism Research Paper
• Media Research Paper
• Public Relations Research Paper
• Public Speaking Research Paper

Crime Research Paper Examples

The crime research paper examples provided by iResearchNet investigate various aspects of criminal behavior and the factors contributing to crime. These papers cover a range of topics, from theoretical analyses of criminality to empirical studies on crime prevention strategies.

• Computer Crime Research Paper
• Domestic Violence Research Paper
• Hate Crimes Research Paper
• Organized Crime Research Paper
• White-Collar Crime Research Paper

Criminal Justice Research Paper Examples

Our criminal justice research paper examples delve into the functioning of the criminal justice system, exploring issues related to law enforcement, the judiciary, and corrections. These papers critically examine policies, practices, and reforms within the criminal justice system.

• Capital Punishment Research Paper
• Community Policing Research Paper
• Corporal Punishment Research Paper
• Criminal Investigation Research Paper
• Criminal Justice System Research Paper
• Plea Bargaining Research Paper
• Restorative Justice Research Paper

Criminal Law Research Paper Examples

These examples focus on the legal aspects of criminal behavior, discussing laws, regulations, and case law that govern criminal proceedings. The papers provide an in-depth analysis of criminal law principles, legal defenses, and the implications of legal decisions.

• Actus Reus Research Paper
• Gun Control Research Paper
• Insanity Defense Research Paper
• International Criminal Law Research Paper
• Self-Defense Research Paper

Criminology Research Paper Examples

iResearchNet’s criminology research paper examples study the causes, prevention, and societal impacts of crime. These papers employ various theoretical frameworks to analyze crime trends and propose effective crime reduction strategies.

• Cultural Criminology Research Paper
• Education and Crime Research Paper
• Marxist Criminology Research Paper
• School Crime Research Paper
• Urban Crime Research Paper

Culture Research Paper Examples

The culture research paper examples examine the beliefs, practices, and artifacts that define different societies. These papers explore how culture shapes identities, influences behaviors, and impacts social interactions.

• Advertising and Culture Research Paper
• Material Culture Research Paper
• Popular Culture Research Paper
• Cross-Cultural Studies Research Paper
• Culture Change Research Paper

Economics Research Paper Examples

Our economics research paper examples offer insights into the functioning of economies at both the micro and macro levels. Topics include economic theory, policy analysis, and the examination of economic indicators and trends.

• Budget Research Paper
• Cost-Benefit Analysis Research Paper
• Fiscal Policy Research Paper
• Labor Market Research Paper

Education Research Paper Examples

These examples address a wide range of issues in education, from teaching methods and curriculum design to educational policy and reform. The papers aim to enhance understanding and improve outcomes in educational settings.

• Early Childhood Education Research Paper
• Information Processing Research Paper
• Multicultural Education Research Paper
• Special Education Research Paper
• Standardized Tests Research Paper

Health Research Paper Examples

The health research paper examples focus on public health issues, healthcare systems, and medical interventions. These papers contribute to the discourse on health promotion, disease prevention, and healthcare management.

• AIDS Research Paper
• Alcoholism Research Paper
• Disease Research Paper
• Health Economics Research Paper
• Health Insurance Research Paper
• Nursing Research Paper

History Research Paper Examples

Our history research paper examples cover significant events, figures, and periods, offering critical analyses of historical narratives and their impact on present-day society.

• Adolf Hitler Research Paper
• American Revolution Research Paper
• Ancient Greece Research Paper
• Apartheid Research Paper
• Christopher Columbus Research Paper
• Climate Change Research Paper
• Cold War Research Paper
• Columbian Exchange Research Paper
• Deforestation Research Paper
• Diseases Research Paper
• Earthquakes Research Paper
• Egypt Research Paper

Leadership Research Paper Examples

These examples explore the theories and practices of effective leadership, examining the qualities, behaviors, and strategies that distinguish successful leaders in various contexts.

• Implicit Leadership Theories Research Paper
• Judicial Leadership Research Paper
• Leadership Styles Research Paper
• Police Leadership Research Paper
• Political Leadership Research Paper
• Remote Leadership Research Paper

Mental Health Research Paper Examples

The mental health research paper examples provided by iResearchNet discuss psychological disorders, therapeutic interventions, and mental health advocacy. These papers aim to raise awareness and improve mental health care practices.

• ADHD Research Paper
• Anxiety Research Paper
• Autism Research Paper
• Depression Research Paper
• Eating Disorders Research Paper
• PTSD Research Paper
• Schizophrenia Research Paper
• Stress Research Paper

Political Science Research Paper Examples

Our political science research paper examples analyze political systems, behaviors, and ideologies. Topics include governance, policy analysis, and the study of political movements and institutions.

• American Government Research Paper
• Civil War Research Paper
• Communism Research Paper
• Democracy Research Paper
• Game Theory Research Paper
• Human Rights Research Paper
• International Relations Research Paper
• Terrorism Research Paper

Psychology Research Paper Examples

These examples delve into the study of the mind and behavior, covering a broad range of topics in clinical, cognitive, developmental, and social psychology.

• Artificial Intelligence Research Paper
• Assessment Psychology Research Paper
• Biological Psychology Research Paper
• Clinical Psychology Research Paper
• Cognitive Psychology Research Paper
• Developmental Psychology Research Paper
• Discrimination Research Paper
• Educational Psychology Research Paper
• Environmental Psychology Research Paper
• Experimental Psychology Research Paper
• Intelligence Research Paper
• Learning Disabilities Research Paper
• Personality Psychology Research Paper
• Psychiatry Research Paper
• Psychotherapy Research Paper
• Social Cognition Research Paper
• Social Psychology Research Paper

Sociology Research Paper Examples

The sociology research paper examples examine societal structures, relationships, and processes. These papers provide insights into social phenomena, inequality, and change.

• Family Research Paper
• Demography Research Paper
• Group Dynamics Research Paper
• Quality of Life Research Paper
• Social Change Research Paper
• Social Movements Research Paper
• Social Networks Research Paper

Technology Research Paper Examples

Our technology research paper examples address the impact of technological advancements on society, exploring issues related to digital communication, cybersecurity, and innovation.

• Computer Forensics Research Paper
• Genetic Engineering Research Paper
• History of Technology Research Paper
• Internet Research Paper
• Nanotechnology Research Paper

Other Research Paper Examples

• Abortion Research Paper
• Adoption Research Paper
• Animal Testing Research Paper
• Bullying Research Paper
• Diversity Research Paper
• Divorce Research Paper
• Drugs Research Paper
• Environmental Issues Research Paper
• Ethics Research Paper
• Evolution Research Paper
• Feminism Research Paper
• Food Research Paper
• Gender Research Paper
• Globalization Research Paper
• Juvenile Justice Research Paper
• Law Research Paper
• Management Research Paper
• Philosophy Research Paper
• Public Health Research Paper
• Religion Research Paper
• Science Research Paper
• Social Sciences Research Paper
• Statistics Research Paper
• Other Sample Research Papers

Each category of research paper examples provided by iResearchNet serves as a valuable resource for students and researchers seeking to deepen their understanding of a specific field. By offering a comprehensive collection of well-researched and thoughtfully written papers, iResearchNet aims to support academic growth and encourage scholarly inquiry across diverse disciplines.

Sample Research Papers: To Read or Not to Read?

When you get an assignment to write a research paper, the first question you ask yourself is ‘Should I look for research paper examples?’ Maybe, I can deal with this task on my own without any help. Is it that difficult?

Thousands of students turn to our service every day for help. It does not mean that they cannot do their assignments on their own. They can, but the reason is different. Writing a research paper demands so much time and energy that asking for assistance seems to be a perfect solution. As the matter of fact, it is a perfect solution, especially, when you need to work to pay for your studying as well.

Firstly, if you search for research paper examples before you start writing, you can save your time significantly. You look at the example and you understand the gist of your assignment within several minutes. Secondly, when you examine some sample paper, you get to know all the requirements. You analyze the structure, the language, and the formatting details. Finally, reading examples helps students to overcome writer’s block, as other people’s ideas can motivate you to discover your own ideas.

The significance of research paper examples in the academic journey of students cannot be overstated. These examples serve not only as a blueprint for structuring and formatting academic papers but also as a beacon guiding students through the complex landscape of academic writing standards. iResearchNet recognizes the pivotal role that high-quality research paper examples play in fostering academic success and intellectual growth among students.

Blueprint for Academic Success

Research paper examples provided by iResearchNet are meticulously crafted to demonstrate the essential elements of effective academic writing. These examples offer clear insights into how to organize a paper, from the introductory paragraph, through the development of arguments and analysis, to the concluding remarks. They showcase the appropriate use of headings, subheadings, and the integration of tables, figures, and appendices, which collectively contribute to a well-organized and coherent piece of scholarly work. By studying these examples, students can gain a comprehensive understanding of the structure and formatting required in academic papers, which is crucial for meeting the rigorous standards of academic institutions.

Sparking Ideas and Providing Evidence

Beyond serving as a structural guide, research paper examples act as a source of inspiration for students embarking on their research projects. These examples illuminate a wide array of topics, methodologies, and analytical frameworks, thereby sparking ideas for students’ own research inquiries. They demonstrate how to effectively engage with existing literature, frame research questions, and develop a compelling thesis statement. Moreover, by presenting evidence and arguments in a logical and persuasive manner, these examples illustrate the art of substantiating claims with solid research, encouraging students to adopt a similar level of rigor and depth in their work.

Enhancing Research Skills

Engagement with high-quality research paper examples is instrumental in improving research skills among students. These examples expose students to various research methodologies, from qualitative case studies to quantitative analyses, enabling them to appreciate the breadth of research approaches applicable to their fields of study. By analyzing these examples, students learn how to critically evaluate sources, differentiate between primary and secondary data, and apply ethical considerations in research. Furthermore, these papers serve as a model for effectively citing sources, thereby teaching students the importance of academic integrity and the avoidance of plagiarism.

In essence, research paper examples are a fundamental resource that can significantly enhance the academic writing and research capabilities of students. iResearchNet’s commitment to providing access to a diverse collection of exemplary papers reflects its dedication to supporting academic excellence. Through these examples, students are equipped with the tools necessary to navigate the challenges of academic writing, foster innovative thinking, and contribute meaningfully to the scholarly community. By leveraging these resources, students can elevate their academic pursuits, ensuring their research is not only rigorous but also impactful.

Custom Research Paper Writing Services

In the academic journey, the ability to craft a compelling and meticulously researched paper is invaluable. Recognizing the challenges and pressures that students face, iResearchNet has developed a suite of research paper writing services designed to alleviate the burden of academic writing and research. Our services are tailored to meet the diverse needs of students across all academic disciplines, ensuring that every research paper not only meets but exceeds the rigorous standards of scholarly excellence. Below, we detail the multifaceted aspects of our research paper writing services, illustrating how iResearchNet stands as a beacon of support in the academic landscape.

At iResearchNet, we understand the pivotal role that research papers play in the academic and professional development of students. With this understanding at our core, we offer comprehensive writing services that cater to the intricate process of research paper creation. Our services are designed to guide students through every stage of the writing process, from initial research to final submission, ensuring clarity, coherence, and scholarly rigor.

The Need for Research Paper Writing Services

Navigating the complexities of academic writing and research can be a daunting task for many students. The challenges of identifying credible sources, synthesizing information, adhering to academic standards, and articulating arguments cohesively are significant. Furthermore, the pressures of tight deadlines and the high stakes of academic success can exacerbate the difficulties faced by students. iResearchNet’s research paper writing services are crafted to address these challenges head-on, providing expert assistance that empowers students to achieve their academic goals with confidence.

Why Choose iResearchNet

Selecting the right partner for research paper writing is a pivotal decision for students and researchers aiming for academic excellence. iResearchNet stands out as the premier choice for several compelling reasons, each designed to meet the diverse needs of our clientele and ensure their success.

• Expert Writers : At iResearchNet, we pride ourselves on our team of expert writers who are not only masters in their respective fields but also possess a profound understanding of academic writing standards. With advanced degrees and extensive experience, our writers bring depth, insight, and precision to each paper, ensuring that your work is informed by the latest research and methodologies.
• Top Quality : Quality is the cornerstone of our services. We adhere to rigorous quality control processes to ensure that every paper we deliver meets the highest standards of academic excellence. Our commitment to quality means thorough research, impeccable writing, and meticulous proofreading, resulting in work that not only meets but exceeds expectations.
• Customized Solutions : Understanding that each research project has its unique challenges and requirements, iResearchNet offers customized solutions tailored to your specific needs. Whether you’re grappling with a complex research topic, a tight deadline, or specific formatting guidelines, our team is equipped to provide personalized support that aligns with your objectives.
• Affordable Prices : We believe that access to high-quality research paper writing services should not be prohibitive. iResearchNet offers competitive pricing structures designed to provide value without compromising on quality. Our transparent pricing model ensures that you know exactly what you are paying for, with no hidden costs or surprises.
• Timely Delivery : Meeting deadlines is critical in academic writing, and at iResearchNet, we take this seriously. Our efficient processes and dedicated team ensure that your paper is delivered on time, every time, allowing you to meet your academic deadlines with confidence.
• 24/7 Support : Our commitment to your success is reflected in our round-the-clock support. Whether you have a question about your order, need to communicate with your writer, or require assistance with any aspect of our service, our friendly and knowledgeable support team is available 24/7 to assist you.
• Money-Back Guarantee : Your satisfaction is our top priority. iResearchNet offers a money-back guarantee, ensuring that if for any reason you are not satisfied with the work delivered, you are entitled to a refund. This policy underscores our confidence in the quality of our services and our dedication to your success.

Choosing iResearchNet for your research paper writing needs means partnering with a trusted provider committed to excellence, innovation, and customer satisfaction. Our unparalleled blend of expert writers, top-quality work, customized solutions, affordability, timely delivery, 24/7 support, and a money-back guarantee makes us the ideal choice for students and researchers seeking to elevate their academic performance.

How It Works: iResearchNet’s Streamlined Process

Navigating the process of obtaining a top-notch research paper has never been more straightforward, thanks to iResearchNet’s streamlined approach. Our user-friendly system ensures that from the moment you decide to place your order to the final receipt of your custom-written paper, every step is seamless, transparent, and tailored to your needs. Here’s how our comprehensive process works:

• Place Your Order : Begin your journey to academic success by visiting our website and filling out the order form. Here, you’ll provide details about your research paper, including the topic, academic level, number of pages, formatting style, and any specific instructions or requirements. This initial step is crucial for us to understand your needs fully and match you with the most suitable writer.
• Make Payment : Once your order details are confirmed, you’ll proceed to the payment section. Our platform offers a variety of secure payment options, ensuring that your transaction is safe and hassle-free. Our transparent pricing policy means you’ll know exactly what you’re paying for upfront, with no hidden fees.
• Choose Your Writer : After payment, you’ll have the opportunity to choose a writer from our team of experts. Our writers are categorized based on their fields of expertise, academic qualifications, and customer feedback ratings. This step empowers you to select the writer who best matches your research paper’s requirements, ensuring a personalized and targeted approach to your project.
• Receive Your Work : Our writer will commence work on your research paper, adhering to the specified guidelines and timelines. Throughout this process, you’ll have the ability to communicate directly with your writer, allowing for updates, revisions, and clarifications to ensure the final product meets your expectations. Once completed, your research paper will undergo a thorough quality check before being delivered to you via your chosen method.
• Free Revisions : Your satisfaction is our priority. Upon receiving your research paper, you’ll have the opportunity to review the work and request any necessary revisions. iResearchNet offers free revisions within a specified period, ensuring that your final paper perfectly aligns with your academic requirements and expectations.

Our process is designed to provide you with a stress-free experience and a research paper that reflects your academic goals. From placing your order to enjoying the success of a well-written paper, iResearchNet is here to support you every step of the way.

Our Extras: Enhancing Your iResearchNet Experience

At iResearchNet, we are committed to offering more than just standard research paper writing services. We understand the importance of providing a comprehensive and personalized experience for each of our clients. That’s why we offer a range of additional services designed to enhance your experience and ensure your academic success. Here are the exclusive extras you can benefit from:

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• Plagiarism Report : Integrity and originality are paramount in academic writing. To provide you with peace of mind, we offer a detailed plagiarism report with every research paper. This report is generated using advanced plagiarism detection software, ensuring that your work is unique and adheres to the highest standards of academic honesty.
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A research paper is an academic piece of writing, so you need to follow all the requirements and standards. Otherwise, it will be impossible to get the high results. To make it easier for you, we have analyzed the structure and peculiarities of a sample research paper on the topic ‘Child Abuse’.

The paper includes 7300+ words, a detailed outline, citations are in APA formatting style, and bibliography with 28 sources.

To write any paper you need to write a great outline. This is the key to a perfect paper. When you organize your paper, it is easier for you to present the ideas logically, without jumping from one thought to another.

In the outline, you need to name all the parts of your paper. That is to say, an introduction, main body, conclusion, bibliography, some papers require abstract and proposal as well.

A good outline will serve as a guide through your paper making it easier for the reader to follow your ideas.

I. Introduction

Ii. estimates of child abuse: methodological limitations, iii. child abuse and neglect: the legalities, iv. corporal punishment versus child abuse, v. child abuse victims: the patterns, vi. child abuse perpetrators: the patterns, vii. explanations for child abuse, viii. consequences of child abuse and neglect, ix. determining abuse: how to tell whether a child is abused or neglected, x. determining abuse: interviewing children, xi. how can society help abused children and abusive families, introduction.

An introduction should include a thesis statement and the main points that you will discuss in the paper.

A thesis statement is one sentence in which you need to show your point of view. You will then develop this point of view through the whole piece of work:

‘The impact of child abuse affects more than one’s childhood, as the psychological and physical injuries often extend well into adulthood.’

Child abuse is a very real and prominent social problem today. The impact of child abuse affects more than one’s childhood, as the psychological and physical injuries often extend well into adulthood. Most children are defenseless against abuse, are dependent on their caretakers, and are unable to protect themselves from these acts.

Childhood serves as the basis for growth, development, and socialization. Throughout adolescence, children are taught how to become productive and positive, functioning members of society. Much of the socializing of children, particularly in their very earliest years, comes at the hands of family members. Unfortunately, the messages conveyed to and the actions against children by their families are not always the positive building blocks for which one would hope.

In 2008, the Children’s Defense Fund reported that each day in America, 2,421 children are confirmed as abused or neglected, 4 children are killed by abuse or neglect, and 78 babies die before their first birthday. These daily estimates translate into tremendous national figures. In 2006, caseworkers substantiated an estimated 905,000 reports of child abuse or neglect. Of these, 64% suffered neglect, 16% were physically abused, 9% were sexually abused, 7% were emotionally or psychologically maltreated, and 2% were medically neglected. In addition, 15% of the victims experienced “other” types of maltreatment such as abandonment, threats of harm to the child, and congenital drug addiction (National Child Abuse and Neglect Data System, 2006). Obviously, this problem is a substantial one.

In the main body, you dwell upon the topic of your paper. You provide your ideas and support them with evidence. The evidence include all the data and material you have found, analyzed and systematized. You can support your point of view with different statistical data, with surveys, and the results of different experiments. Your task is to show that your idea is right, and make the reader interested in the topic.

In this example, a writer analyzes the issue of child abuse: different statistical data, controversies regarding the topic, examples of the problem and the consequences.

Several issues arise when considering the amount of child abuse that occurs annually in the United States. Child abuse is very hard to estimate because much (or most) of it is not reported. Children who are abused are unlikely to report their victimization because they may not know any better, they still love their abusers and do not want to see them taken away (or do not themselves want to be taken away from their abusers), they have been threatened into not reporting, or they do not know to whom they should report their victimizations. Still further, children may report their abuse only to find the person to whom they report does not believe them or take any action on their behalf. Continuing to muddy the waters, child abuse can be disguised as legitimate injury, particularly because young children are often somewhat uncoordinated and are still learning to accomplish physical tasks, may not know their physical limitations, and are often legitimately injured during regular play. In the end, children rarely report child abuse; most often it is an adult who makes a report based on suspicion (e.g., teacher, counselor, doctor, etc.).

Even when child abuse is reported, social service agents and investigators may not follow up or substantiate reports for a variety of reasons. Parents can pretend, lie, or cover up injuries or stories of how injuries occurred when social service agents come to investigate. Further, there is not always agreement about what should be counted as abuse by service providers and researchers. In addition, social service agencies/agents have huge caseloads and may only be able to deal with the most serious forms of child abuse, leaving the more “minor” forms of abuse unsupervised and unmanaged (and uncounted in the statistical totals).

While most laws about child abuse and neglect fall at the state levels, federal legislation provides a foundation for states by identifying a minimum set of acts and behaviors that define child abuse and neglect. The Federal Child Abuse Prevention and Treatment Act (CAPTA), which stems from the Keeping Children and Families Safe Act of 2003, defines child abuse and neglect as, at minimum, “(1) any recent act or failure to act on the part of a parent or caretaker which results in death, serious physical or emotional harm, sexual abuse, or exploitation; or (2) an act or failure to act which presents an imminent risk or serious harm.”

Using these minimum standards, each state is responsible for providing its own definition of maltreatment within civil and criminal statutes. When defining types of child abuse, many states incorporate similar elements and definitions into their legal statutes. For example, neglect is often defined as failure to provide for a child’s basic needs. Neglect can encompass physical elements (e.g., failure to provide necessary food or shelter, or lack of appropriate supervision), medical elements (e.g., failure to provide necessary medical or mental health treatment), educational elements (e.g., failure to educate a child or attend to special educational needs), and emotional elements (e.g., inattention to a child’s emotional needs, failure to provide psychological care, or permitting the child to use alcohol or other drugs). Failure to meet needs does not always mean a child is neglected, as situations such as poverty, cultural values, and community standards can influence the application of legal statutes. In addition, several states distinguish between failure to provide based on financial inability and failure to provide for no apparent financial reason.

Statutes on physical abuse typically include elements of physical injury (ranging from minor bruises to severe fractures or death) as a result of punching, beating, kicking, biting, shaking, throwing, stabbing, choking, hitting (with a hand, stick, strap, or other object), burning, or otherwise harming a child. Such injury is considered abuse regardless of the intention of the caretaker. In addition, many state statutes include allowing or encouraging another person to physically harm a child (such as noted above) as another form of physical abuse in and of itself. Sexual abuse usually includes activities by a parent or caretaker such as fondling a child’s genitals, penetration, incest, rape, sodomy, indecent exposure, and exploitation through prostitution or the production of pornographic materials.

Finally, emotional or psychological abuse typically is defined as a pattern of behavior that impairs a child’s emotional development or sense of self-worth. This may include constant criticism, threats, or rejection, as well as withholding love, support, or guidance. Emotional abuse is often the most difficult to prove and, therefore, child protective services may not be able to intervene without evidence of harm to the child. Some states suggest that harm may be evidenced by an observable or substantial change in behavior, emotional response, or cognition, or by anxiety, depression, withdrawal, or aggressive behavior. At a practical level, emotional abuse is almost always present when other types of abuse are identified.

Some states include an element of substance abuse in their statutes on child abuse. Circumstances that can be considered substance abuse include (a) the manufacture of a controlled substance in the presence of a child or on the premises occupied by a child (Colorado, Indiana, Iowa, Montana, South Dakota, Tennessee, and Virginia); (b) allowing a child to be present where the chemicals or equipment for the manufacture of controlled substances are used (Arizona, New Mexico); (c) selling, distributing, or giving drugs or alcohol to a child (Florida, Hawaii, Illinois, Minnesota, and Texas); (d) use of a controlled substance by a caregiver that impairs the caregiver’s ability to adequately care for the child (Kentucky, New York, Rhode Island, and Texas); and (e) exposure of the child to drug paraphernalia (North Dakota), the criminal sale or distribution of drugs (Montana, Virginia), or drug-related activity (District of Columbia).

One of the most difficult issues with which the U.S. legal system must contend is that of allowing parents the right to use corporal punishment when disciplining a child, while not letting them cross over the line into the realm of child abuse. Some parents may abuse their children under the guise of discipline, and many instances of child abuse arise from angry parents who go too far when disciplining their children with physical punishment. Generally, state statutes use terms such as “reasonable discipline of a minor,” “causes only temporary, short-term pain,” and may cause “the potential for bruising” but not “permanent damage, disability, disfigurement or injury” to the child as ways of indicating the types of discipline behaviors that are legal. However, corporal punishment that is “excessive,” “malicious,” “endangers the bodily safety of,” or is “an intentional infliction of injury” is not allowed under most state statutes (e.g., state of Florida child abuse statute).

Most research finds that the use of physical punishment (most often spanking) is not an effective method of discipline. The literature on this issue tends to find that spanking stops misbehavior, but no more effectively than other firm measures. Further, it seems to hinder rather than improve general compliance/obedience (particularly when the child is not in the presence of the punisher). Researchers have also explained why physical punishment is not any more effective at gaining child compliance than nonviolent forms of discipline. Some of the problems that arise when parents use spanking or other forms of physical punishment include the fact that spanking does not teach what children should do, nor does it provide them with alternative behavior options should the circumstance arise again. Spanking also undermines reasoning, explanation, or other forms of parental instruction because children cannot learn, reason, or problem solve well while experiencing threat, pain, fear, or anger. Further, the use of physical punishment is inconsistent with nonviolent principles, or parental modeling. In addition, the use of spanking chips away at the bonds of affection between parents and children, and tends to induce resentment and fear. Finally, it hinders the development of empathy and compassion in children, and they do not learn to take responsibility for their own behavior (Pitzer, 1997).

One of the biggest problems with the use of corporal punishment is that it can escalate into much more severe forms of violence. Usually, parents spank because they are angry (and somewhat out of control) and they can’t think of other ways to discipline. When parents are acting as a result of emotional triggers, the notion of discipline is lost while punishment and pain become the foci.

In 2006, of the children who were found to be victims of child abuse, nearly 75% of them were first-time victims (or had not come to the attention of authorities prior). A slight majority of child abuse victims were girls—51.5%, compared to 48% of abuse victims being boys. The younger the child, the more at risk he or she is for child abuse and neglect victimization. Specifically, the rate for infants (birth to 1 year old) was approximately 24 per 1,000 children of the same age group. The victimization rate for children 1–3 years old was 14 per 1,000 children of the same age group. The abuse rate for children aged 4– 7 years old declined further to 13 per 1,000 children of the same age group. African American, American Indian, and Alaska Native children, as well as children of multiple races, had the highest rates of victimization. White and Latino children had lower rates, and Asian children had the lowest rates of child abuse and neglect victimization. Regarding living arrangements, nearly 27% of victims were living with a single mother, 20% were living with married parents, while 22% were living with both parents but the marital status was unknown. (This reporting element had nearly 40% missing data, however.) Regarding disability, nearly 8% of child abuse victims had some degree of mental retardation, emotional disturbance, visual or hearing impairment, learning disability, physical disability, behavioral problems, or other medical problems. Unfortunately, data indicate that for many victims, the efforts of the child protection services system were not successful in preventing subsequent victimization. Children who had been prior victims of maltreatment were 96% more likely to experience another occurrence than those who were not prior victims. Further, child victims who were reported to have a disability were 52% more likely to experience recurrence than children without a disability. Finally, the oldest victims (16–21 years of age) were the least likely to experience a recurrence, and were 51% less likely to be victimized again than were infants (younger than age 1) (National Child Abuse and Neglect Data System, 2006).

Child fatalities are the most tragic consequence of maltreatment. Yet, each year, children die from abuse and neglect. In 2006, an estimated 1,530 children in the United States died due to abuse or neglect. The overall rate of child fatalities was 2 deaths per 100,000 children. More than 40% of child fatalities were attributed to neglect, but physical abuse also was a major contributor. Approximately 78% of the children who died due to child abuse and neglect were younger than 4 years old, and infant boys (younger than 1) had the highest rate of fatalities at 18.5 deaths per 100,000 boys of the same age in the national population. Infant girls had a rate of 14.7 deaths per 100,000 girls of the same age (National Child Abuse and Neglect Data System, 2006).

One question to be addressed regarding child fatalities is why infants have such a high rate of death when compared to toddlers and adolescents. Children under 1 year old pose an immense amount of responsibility for their caretakers: they are completely dependent and need constant attention. Children this age are needy, impulsive, and not amenable to verbal control or effective communication. This can easily overwhelm vulnerable parents. Another difficulty associated with infants is that they are physically weak and small. Injuries to infants can be fatal, while similar injuries to older children might not be. The most common cause of death in children less than 1 year is cerebral trauma (often the result of shaken-baby syndrome). Exasperated parents can deliver shakes or blows without realizing how little it takes to cause irreparable or fatal damage to an infant. Research informs us that two of the most common triggers for fatal child abuse are crying that will not cease and toileting accidents. Both of these circumstances are common in infants and toddlers whose only means of communication often is crying, and who are limited in mobility and cannot use the toilet. Finally, very young children cannot assist in injury diagnoses. Children who have been injured due to abuse or neglect often cannot communicate to medical professionals about where it hurts, how it hurts, and so forth. Also, nonfatal injuries can turn fatal in the absence of care by neglectful parents or parents who do not want medical professionals to possibly identify an injury as being the result of abuse.

Estimates reveal that nearly 80% of perpetrators of child abuse were parents of the victim. Other relatives accounted for nearly 7%, and unmarried partners of parents made up 4% of perpetrators. Of those perpetrators that were parents, over 90% were biological parents, 4% were stepparents, and 0.7% were adoptive parents. Of this group, approximately 58% of perpetrators were women and 42% were men. Women perpetrators are typically younger than men. The average age for women abusers was 31 years old, while for men the average was 34 years old. Forty percent of women who abused were younger than 30 years of age, compared with 33% of men being under 30. The racial distribution of perpetrators is similar to that of victims. Fifty-four percent were white, 21% were African American, and 20% were Hispanic/Latino (National Child Abuse and Neglect Data System, 2006).

There are many factors that are associated with child abuse. Some of the more common/well-accepted explanations are individual pathology, parent–child interaction, past abuse in the family (or social learning), situational factors, and cultural support for physical punishment along with a lack of cultural support for helping parents here in the United States.

The first explanation centers on the individual pathology of a parent or caretaker who is abusive. This theory focuses on the idea that people who abuse their children have something wrong with their individual personality or biological makeup. Such psychological pathologies may include having anger control problems; being depressed or having post-partum depression; having a low tolerance for frustration (e.g., children can be extremely frustrating: they don’t always listen; they constantly push the line of how far they can go; and once the line has been established, they are constantly treading on it to make sure it hasn’t moved. They are dependent and self-centered, so caretakers have very little privacy or time to themselves); being rigid (e.g., having no tolerance for differences—for example, what if your son wanted to play with dolls? A rigid father would not let him, laugh at him for wanting to, punish him when he does, etc.); having deficits in empathy (parents who cannot put themselves in the shoes of their children cannot fully understand what their children need emotionally); or being disorganized, inefficient, and ineffectual. (Parents who are unable to manage their own lives are unlikely to be successful at managing the lives of their children, and since many children want and need limits, these parents are unable to set them or adhere to them.)

Biological pathologies that may increase the likelihood of someone becoming a child abuser include having substance abuse or dependence problems, or having persistent or reoccurring physical health problems (especially health problems that can be extremely painful and can cause a person to become more self-absorbed, both qualities that can give rise to a lack of patience, lower frustration tolerance, and increased stress).

The second explanation for child abuse centers on the interaction between the parent and the child, noting that certain types of parents are more likely to abuse, and certain types of children are more likely to be abused, and when these less-skilled parents are coupled with these more difficult children, child abuse is the most likely to occur. Discussion here focuses on what makes a parent less skilled, and what makes a child more difficult. Characteristics of unskilled parents are likely to include such traits as only pointing out what children do wrong and never giving any encouragement for good behavior, and failing to be sensitive to the emotional needs of children. Less skilled parents tend to have unrealistic expectations of children. They may engage in role reversal— where the parents make the child take care of them—and view the parent’s happiness and well-being as the responsibility of the child. Some parents view the parental role as extremely stressful and experience little enjoyment from being a parent. Finally, less-skilled parents tend to have more negative perceptions regarding their child(ren). For example, perhaps the child has a different shade of skin than they expected and this may disappoint or anger them, they may feel the child is being manipulative (long before children have this capability), or they may view the child as the scapegoat for all the parents’ or family’s problems. Theoretically, parents with these characteristics would be more likely to abuse their children, but if they are coupled with having a difficult child, they would be especially likely to be abusive. So, what makes a child more difficult? Certainly, through no fault of their own, children may have characteristics that are associated with child care that is more demanding and difficult than in the “normal” or “average” situation. Such characteristics can include having physical and mental disabilities (autism, attention deficit hyperactivity disorder [ADHD], hyperactivity, etc.); the child may be colicky, frequently sick, be particularly needy, or cry more often. In addition, some babies are simply unhappier than other babies for reasons that cannot be known. Further, infants are difficult even in the best of circumstances. They are unable to communicate effectively, and they are completely dependent on their caretakers for everything, including eating, diaper changing, moving around, entertainment, and emotional bonding. Again, these types of children, being more difficult, are more likely to be victims of child abuse.

Nonetheless, each of these types of parents and children alone cannot explain the abuse of children, but it is the interaction between them that becomes the key. Unskilled parents may produce children that are happy and not as needy, and even though they are unskilled, they do not abuse because the child takes less effort. At the same time, children who are more difficult may have parents who are skilled and are able to handle and manage the extra effort these children take with aplomb. However, risks for child abuse increase when unskilled parents must contend with difficult children.

Social learning or past abuse in the family is a third common explanation for child abuse. Here, the theory concentrates not only on what children learn when they see or experience violence in their homes, but additionally on what they do not learn as a result of these experiences. Social learning theory in the context of family violence stresses that if children are abused or see abuse (toward siblings or a parent), those interactions and violent family members become the representations and role models for their future familial interactions. In this way, what children learn is just as important as what they do not learn. Children who witness or experience violence may learn that this is the way parents deal with children, or that violence is an acceptable method of child rearing and discipline. They may think when they become parents that “violence worked on me when I was a child, and I turned out fine.” They may learn unhealthy relationship interaction patterns; children may witness the negative interactions of parents and they may learn the maladaptive or violent methods of expressing anger, reacting to stress, or coping with conflict.

What is equally as important, though, is that they are unlikely to learn more acceptable and nonviolent ways of rearing children, interacting with family members, and working out conflict. Here it may happen that an adult who was abused as a child would like to be nonviolent toward his or her own children, but when the chips are down and the child is misbehaving, this abused-child-turned-adult does not have a repertoire of nonviolent strategies to try. This parent is more likely to fall back on what he or she knows as methods of discipline.

Something important to note here is that not all abused children grow up to become abusive adults. Children who break the cycle were often able to establish and maintain one healthy emotional relationship with someone during their childhoods (or period of young adulthood). For instance, they may have received emotional support from a nonabusing parent, or they received social support and had a positive relationship with another adult during their childhood (e.g., teacher, coach, minister, neighbor, etc.). Abused children who participate in therapy during some period of their lives can often break the cycle of violence. In addition, adults who were abused but are able to form an emotionally supportive and satisfying relationship with a mate can make the transition to being nonviolent in their family interactions.

Moving on to a fourth familiar explanation for child abuse, there are some common situational factors that influence families and parents and increase the risks for child abuse. Typically, these are factors that increase family stress or social isolation. Specifically, such factors may include receiving public assistance or having low socioeconomic status (a combination of low income and low education). Other factors include having family members who are unemployed, underemployed (working in a job that requires lower qualifications than an individual possesses), or employed only part time. These financial difficulties cause great stress for families in meeting the needs of the individual members. Other stress-inducing familial characteristics are single-parent households and larger family size. Finally, social isolation can be devastating for families and family members. Having friends to talk to, who can be relied upon, and with whom kids can be dropped off occasionally is tremendously important for personal growth and satisfaction in life. In addition, social isolation and stress can cause individuals to be quick to lose their tempers, as well as cause people to be less rational in their decision making and to make mountains out of mole hills. These situations can lead families to be at greater risk for child abuse.

Finally, cultural views and supports (or lack thereof) can lead to greater amounts of child abuse in a society such as the United States. One such cultural view is that of societal support for physical punishment. This is problematic because there are similarities between the way criminals are dealt with and the way errant children are handled. The use of capital punishment is advocated for seriously violent criminals, and people are quick to use such idioms as “spare the rod and spoil the child” when it comes to the discipline or punishment of children. In fact, it was not until quite recently that parenting books began to encourage parents to use other strategies than spanking or other forms of corporal punishment in the discipline of their children. Only recently, the American Academy of Pediatrics has come out and recommended that parents do not spank or use other forms of violence on their children because of the deleterious effects such methods have on youngsters and their bonds with their parents. Nevertheless, regardless of recommendations, the culture of corporal punishment persists.

Another cultural view in the United States that can give rise to greater incidents of child abuse is the belief that after getting married, couples of course should want and have children. Culturally, Americans consider that children are a blessing, raising kids is the most wonderful thing a person can do, and everyone should have children. Along with this notion is the idea that motherhood is always wonderful; it is the most fulfilling thing a woman can do; and the bond between a mother and her child is strong, glorious, and automatic—all women love being mothers. Thus, culturally (and theoretically), society nearly insists that married couples have children and that they will love having children. But, after children are born, there is not much support for couples who have trouble adjusting to parenthood, or who do not absolutely love their new roles as parents. People look askance at parents who need help, and cannot believe parents who say anything negative about parenthood. As such, theoretically, society has set up a situation where couples are strongly encouraged to have kids, are told they will love kids, but then society turns a blind or disdainful eye when these same parents need emotional, financial, or other forms of help or support. It is these types of cultural viewpoints that increase the risks for child abuse in society.

The consequences of child abuse are tremendous and long lasting. Research has shown that the traumatic experience of childhood abuse is life changing. These costs may surface during adolescence, or they may not become evident until abused children have grown up and become abusing parents or abused spouses. Early identification and treatment is important to minimize these potential long-term effects. Whenever children say they have been abused, it is imperative that they be taken seriously and their abuse be reported. Suspicions of child abuse must be reported as well. If there is a possibility that a child is or has been abused, an investigation must be conducted.

Children who have been abused may exhibit traits such as the inability to love or have faith in others. This often translates into adults who are unable to establish lasting and stable personal relationships. These individuals have trouble with physical closeness and touching as well as emotional intimacy and trust. Further, these qualities tend to cause a fear of entering into new relationships, as well as the sabotaging of any current ones.

Psychologically, children who have been abused tend to have poor self-images or are passive, withdrawn, or clingy. They may be angry individuals who are filled with rage, anxiety, and a variety of fears. They are often aggressive, disruptive, and depressed. Many abused children have flashbacks and nightmares about the abuse they have experienced, and this may cause sleep problems as well as drug and alcohol problems. Posttraumatic stress disorder (PTSD) and antisocial personality disorder are both typical among maltreated children. Research has also shown that most abused children fail to reach “successful psychosocial functioning,” and are thus not resilient and do not resume a “normal life” after the abuse has ended.

Socially (and likely because of these psychological injuries), abused children have trouble in school, will have difficulty getting and remaining employed, and may commit a variety of illegal or socially inappropriate behaviors. Many studies have shown that victims of child abuse are likely to participate in high-risk behaviors such as alcohol or drug abuse, the use of tobacco, and high-risk sexual behaviors (e.g., unprotected sex, large numbers of sexual partners). Later in life, abused children are more likely to have been arrested and homeless. They are also less able to defend themselves in conflict situations and guard themselves against repeated victimizations.

Medically, abused children likely will experience health problems due to the high frequency of physical injuries they receive. In addition, abused children experience a great deal of emotional turmoil and stress, which can also have a significant impact on their physical condition. These health problems are likely to continue occurring into adulthood. Some of these longer-lasting health problems include headaches; eating problems; problems with toileting; and chronic pain in the back, stomach, chest, and genital areas. Some researchers have noted that abused children may experience neurological impairment and problems with intellectual functioning, while others have found a correlation between abuse and heart, lung, and liver disease, as well as cancer (Thomas, 2004).

Victims of sexual abuse show an alarming number of disturbances as adults. Some dislike and avoid sex, or experience sexual problems or disorders, while other victims appear to enjoy sexual activities that are self-defeating or maladaptive—normally called “dysfunctional sexual behavior”—and have many sexual partners.

Abused children also experience a wide variety of developmental delays. Many do not reach physical, cognitive, or emotional developmental milestones at the typical time, and some never accomplish what they are supposed to during childhood socialization. In the next section, these developmental delays are discussed as a means of identifying children who may be abused.

There are two primary ways of identifying children who are abused: spotting and evaluating physical injuries, and detecting and appraising developmental delays. Distinguishing physical injuries due to abuse can be difficult, particularly among younger children who are likely to get hurt or receive injuries while they are playing and learning to become ambulatory. Nonetheless, there are several types of wounds that children are unlikely to give themselves during their normal course of play and exploration. These less likely injuries may signal instances of child abuse.

While it is true that children are likely to get bruises, particularly when they are learning to walk or crawl, bruises on infants are not normal. Also, the back of the legs, upper arms, or on the chest, neck, head, or genitals are also locations where bruises are unlikely to occur during normal childhood activity. Further, bruises with clean patterns, like hand prints, buckle prints, or hangers (to name a few), are good examples of the types of bruises children do not give themselves.

Another area of physical injury where the source of the injury can be difficult to detect is fractures. Again, children fall out of trees, or crash their bikes, and can break limbs. These can be normal parts of growing up. However, fractures in infants less than 12 months old are particularly suspect, as infants are unlikely to be able to accomplish the types of movement necessary to actually break a leg or an arm. Further, multiple fractures, particularly more than one on a bone, should be examined more closely. Spiral or torsion fractures (when the bone is broken by twisting) are suspect because when children break their bones due to play injuries, the fractures are usually some other type (e.g., linear, oblique, compacted). In addition, when parents don’t know about the fracture(s) or how it occurred, abuse should be considered, because when children get these types of injuries, they need comfort and attention.

Head and internal injuries are also those that may signal abuse. Serious blows to the head cause internal head injuries, and this is very different from the injuries that result from bumping into things. Abused children are also likely to experience internal injuries like those to the abdomen, liver, kidney, and bladder. They may suffer a ruptured spleen, or intestinal perforation. These types of damages rarely happen by accident.

Burns are another type of physical injury that can happen by accident or by abuse. Nevertheless, there are ways to tell these types of burn injuries apart. The types of burns that should be examined and investigated are those where the burns are in particular locations. Burns to the bottom of the feet, genitals, abdomen, or other inaccessible spots should be closely considered. Burns of the whole hand or those to the buttocks are also unlikely to happen as a result of an accident.

Turning to the detection and appraisal of developmental delays, one can more readily assess possible abuse by considering what children of various ages should be able to accomplish, than by noting when children are delayed and how many milestones on which they are behind schedule. Importantly, a few delays in reaching milestones can be expected, since children develop individually and not always according to the norm. Nonetheless, when children are abused, their development is likely to be delayed in numerous areas and across many milestones.

As children develop and grow, they should be able to crawl, walk, run, talk, control going to the bathroom, write, set priorities, plan ahead, trust others, make friends, develop a good self-image, differentiate between feeling and behavior, and get their needs met in appropriate ways. As such, when children do not accomplish these feats, their circumstances should be examined.

Infants who are abused or neglected typically develop what is termed failure to thrive syndrome. This syndrome is characterized by slow, inadequate growth, or not “filling out” physically. They have a pale, colorless complexion and dull eyes. They are not likely to spend much time looking around, and nothing catches their eyes. They may show other signs of lack of nutrition such as cuts, bruises that do not heal in a timely way, and discolored fingernails. They are also not trusting and may not cry much, as they are not expecting to have their needs met. Older infants may not have developed any language skills, or these developments are quite slow. This includes both verbal and nonverbal means of communication.

Toddlers who are abused often become hypervigilant about their environments and others’ moods. They are more outwardly focused than a typical toddler (who is quite self-centered) and may be unable to separate themselves as individuals, or consider themselves as distinct beings. In this way, abused toddlers cannot focus on tasks at hand because they are too concerned about others’ reactions. They don’t play with toys, have no interest in exploration, and seem unable to enjoy life. They are likely to accept losses with little reaction, and may have age-inappropriate knowledge of sex and sexual relations. Finally, toddlers, whether they are abused or not, begin to mirror their parents’ behaviors. Thus, toddlers who are abused may mimic the abuse when they are playing with dolls or “playing house.”

Developmental delays can also be detected among abused young adolescents. Some signs include the failure to learn cause and effect, since their parents are so inconsistent. They have no energy for learning and have not developed beyond one- or two-word commands. They probably cannot follow complicated directions (such as two to three tasks per instruction), and they are unlikely to be able to think for themselves. Typically, they have learned that failure is totally unacceptable, but they are more concerned with the teacher’s mood than with learning and listening to instruction. Finally, they are apt to have been inadequately toilet trained and thus may be unable to control their bladders.

Older adolescents, because they are likely to have been abused for a longer period of time, continue to get further and further behind in their developmental achievements. Abused children this age become family nurturers. They take care of their parents and cater to their parents’ needs, rather than the other way around. In addition, they probably take care of any younger siblings and do the household chores. Because of these default responsibilities, they usually do not participate in school activities; they frequently miss days at school; and they have few, if any, friends. Because they have become so hypervigilant and have increasingly delayed development, they lose interest in and become disillusioned with education. They develop low self-esteem and little confidence, but seem old for their years. Children this age who are abused are still likely to be unable to control their bladders and may have frequent toileting accidents.

Other developmental delays can occur and be observed in abused and neglected children of any age. For example, malnutrition and withdrawal can be noticed in infants through teenagers. Maltreated children frequently have persistent or untreated illnesses, and these can become permanent disabilities if medical conditions go untreated for a long enough time. Another example can be the consequences of neurological damage. Beyond being a medical issue, this type of damage can cause problems with social behavior and impulse control, which, again, can be discerned in various ages of children.

Once child abuse is suspected, law enforcement officers, child protection workers, or various other practitioners may need to interview the child about the abuse or neglect he or she may have suffered. Interviewing children can be extremely difficult because children at various stages of development can remember only certain parts or aspects of the events in their lives. Also, interviewers must be careful that they do not put ideas or answers into the heads of the children they are interviewing. There are several general recommendations when interviewing children about the abuse they may have experienced. First, interviewers must acknowledge that even when children are abused, they likely still love their parents. They do not want to be taken away from their parents, nor do they want to see their parents get into trouble. Interviewers must not blame the parents or be judgmental about them or the child’s family. Beyond that, interviews should take place in a safe, neutral location. Interviewers can use dolls and role-play to help children express the types of abuse of which they may be victims.

Finally, interviewers must ask age-appropriate questions. For example, 3-year-olds can probably only answer questions about what happened and who was involved. Four- to five-year-olds can also discuss where the incidents occurred. Along with what, who, and where, 6- to 8-year-olds can talk about the element of time, or when the abuse occurred. Nine- to 10-year-olds are able to add commentary about the number of times the abuse occurred. Finally, 11-year-olds and older children can additionally inform interviewers about the circumstances of abusive instances.

A conclusion is not a summary of what a writer has already mentioned. On the contrary, it is the last point made. Taking every detail of the investigation, the researcher makes the concluding point. In this part of a paper, you need to put a full stop in your research. You need to persuade the reader in your opinion.

Never add any new information in the conclusion. You can present solutions to the problem and you dwell upon the results, but only if this information has been already mentioned in the main body.

Child advocates recommend a variety of strategies to aid families and children experiencing abuse. These recommendations tend to focus on societal efforts as well as more individual efforts. One common strategy advocated is the use of public service announcements that encourage individuals to report any suspected child abuse. Currently, many mandatory reporters (those required by law to report abuse such as teachers, doctors, and social service agency employees) and members of communities feel that child abuse should not be reported unless there is substantial evidence that abuse is indeed occurring. Child advocates stress that this notion should be changed, and that people should report child abuse even if it is only suspected. Public service announcements should stress that if people report suspected child abuse, the worst that can happen is that they might be wrong, but in the grander scheme of things that is really not so bad.

Child advocates also stress that greater interagency cooperation is needed. This cooperation should be evident between women’s shelters, child protection agencies, programs for at-risk children, medical agencies, and law enforcement officers. These agencies typically do not share information, and if they did, more instances of child abuse would come to the attention of various authorities and could be investigated and managed. Along these lines, child protection agencies and programs should receive more funding. When budgets are cut, social services are often the first things to go or to get less financial support. Child advocates insist that with more resources, child protection agencies could hire more workers, handle more cases, conduct more investigations, and follow up with more children and families.

Continuing, more educational efforts must be initiated about issues such as punishment and discipline styles and strategies; having greater respect for children; as well as informing the community about what child abuse is, and how to recognize it. In addition, Americans must alter the cultural orientation about child bearing and child rearing. Couples who wish to remain child-free must be allowed to do so without disdain. And, it must be acknowledged that raising children is very difficult, is not always gloriously wonderful, and that parents who seek help should be lauded and not criticized. These kinds of efforts can help more children to be raised in nonviolent, emotionally satisfying families, and thus become better adults.

Bibliography

When you write a paper, make sure you are aware of all the formatting requirements. Incorrect formatting can lower your mark, so do not underestimate the importance of this part.

Organizing your bibliography is quite a tedious and time-consuming task. Still, you need to do it flawlessly. For this reason, analyze all the standards you need to meet or ask professionals to help you with it. All the comas, colons, brackets etc. matter. They truly do.

Bibliography:

• American Academy of Pediatrics: https://www.aap.org/
• Bancroft, L., & Silverman, J. G. (2002). The batterer as parent. Thousand Oaks, CA: Sage.
• Child Abuse Prevention and Treatment Act, 42 U.S.C.A. § 5106g (1998).
• Childhelp: Child Abuse Statistics: https://www.childhelp.org/child-abuse-statistics/
• Children’s Defense Fund: https://www.childrensdefense.org/
• Child Stats.gov: https://www.childstats.gov/
• Child Welfare League of America: https://www.cwla.org/
• Crosson-Tower, C. (2008). Understanding child abuse and neglect (7th ed.). Boston: Allyn & Bacon.
• DeBecker, G. (1999). Protecting the gift: Keeping children and teenagers safe (and parents sane). New York: Bantam Dell.
• Family Research Laboratory at the University of New Hampshire: https://cola.unh.edu/family-research-laboratory
• Guterman, N. B. (2001). Stopping child maltreatment before it starts: Emerging horizons in early home visitation services. Thousand Oaks, CA: Sage.
• Herman, J. L. (2000). Father-daughter incest. Cambridge, MA: Harvard University Press.
• Medline Plus, Child Abuse: https://medlineplus.gov/childabuse.html
• Myers, J. E. B. (Ed.). (1994). The backlash: Child protection under fire. Newbury Park, CA: Sage.
• National Center for Missing and Exploited Children: https://www.missingkids.org/home
• National Child Abuse and Neglect Data System. (2006). Child maltreatment 2006: Reports from the states to the National Child Abuse and Neglect Data System. Washington, DC: U.S. Department of Health and Human Services, Administration for Children and Families.
• New York University Silver School of Social Work: https://socialwork.nyu.edu/
• Pitzer, R. L. (1997). Corporal punishment in the discipline of children in the home: Research update for practitioners. Paper presented at the National Council on Family Relations Annual Conference, Washington, DC.
• RAND, Child Abuse and Neglect: https://www.rand.org/topics/child-abuse-and-neglect.html
• Richards, C. E. (2001). The loss of innocents: Child killers and their victims. Wilmington, DE: Scholarly Resources.
• Straus, M. A. (2001). Beating the devil out of them: Corporal punishment in American families and its effects on children. Edison, NJ: Transaction.
• Thomas, P. M. (2004). Protection, dissociation, and internal roles: Modeling and treating the effects of child abuse. Review of General Psychology, 7(15).
• U.S. Department of Health and Human Services, Administration for Children and Families: https://www.acf.hhs.gov/

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The Ethicist

Can i use a.i. to grade my students’ papers.

The magazine’s Ethicist columnist on artificial intelligence platforms, and whether it’s hypocritical for teachers to use these tools while forbidding students from doing the same.

By Kwame Anthony Appiah

I am a junior-high-school English teacher. In the past school year, there has been a significant increase in students’ cheating on writing assignments by using artificial intelligence. Our department feels that 13-year-old students will only become better writers if they practice and learn from the successes and challenges that come with that.

Recently our department tasked students with writing an argumentative essay, an assignment we supported by breaking down the process into multiple steps. The exercise took several days of class time and homework to complete. All of our students signed a contract agreeing not to use A.I. assistance, and parents promised to support the agreement by monitoring their children when they worked at home. Yet many students still used A.I.

Some of our staff members uploaded their grading rubric into an A.I.-assisted platform, and students uploaded their essays for assessment. The program admittedly has some strengths. Most notable, it gives students writing feedback and the opportunity to edit their work before final submission. The papers are graded within minutes, and the teachers are able to transfer the A.I. grade into their roll book.

I find this to be hypocritical. I spend many hours grading my students’ essays. It’s tedious work, but I feel that it’s my responsibility — if a student makes an effort to complete the task, they should have my undivided attention during the assessment process.

Here’s where I struggle: Should I embrace new technology and use A.I.-assisted grading to save time and my sanity even though I forbid my students from using it? Is it unethical for teachers to ask students not to use A.I. to assist their writing but then allow an A.I. platform to grade their work? — Name Withheld

From the Ethicist:

You have a sound rationale for discouraging your students from using A.I. to draft their essays. As with many other skills, writing well and thinking clearly will improve through practice. By contrast, you already know how to grade papers; you don’t need the practice.

What matters is whether an A.I.-assisted platform can reliably appraise and diagnose your students’ writing, providing the explanation and guidance these students need to improve. In theory, such tools — and I see that there are several on the market, including from major educational publishers — have certain advantages. The hope is that they can grade without inconsistency, without getting tired, without being affected by the expectations that surely affect those of us who hand-grade student work.

I notice you haven’t raised concerns about whether the platform provides reliable assessments; you’ll have to decide if it does. (If it isn’t quite up to snuff, it might become so in a year or two, so your question will persist.) Provided the platform does a decent job of assessment, though, I don’t see why you must do it all yourself. You should review the A.I.-annotated versions of your students’ writing, check that you agree with the output, and make notes of issues to bring up in class. But time saved in evaluating the papers might be better spent on other things — and by “better,” I mean better for the students. There are pedagogical functions, after all, that only you can perform.

In sum: It’s not hypocritical to use A.I. yourself in a way that serves your students well, even as you insist that they don’t use it in a way that serves them badly.

Readers Respond

The previous question was from a reader who asked about professional boundaries. He wrote: “I am a retired, married male psychiatrist. A divorced female former patient of mine contacted me recently, 45 years after her treatment ended. Would it be OK to correspond with her by email? Or is this a case of ‘once a patient, always a patient?’”

In his response, the Ethicist noted: “The relevant professional associations tend to have strictures that are specifically about sexual relationships with former patients. … In light of the potential for exploitation within the therapist-patient relationship, these rules are meant to maintain clear boundaries, protect patient welfare, uphold the integrity of the profession and eliminate any gray areas that could lead to ethical breaches. But though you do mention her marital status, and yours, you’re just asking about emailing her — about establishing friendly relations. The question for you is whether she might be harmed by this, whether whatever knowledge or trust gained from your professional relationship would shadow a personal one. Yes, almost half a century has elapsed since your professional relationship, but you still have to be confident that a correspondence with her clears this bar. If it does, you may email with a clear conscience.” ( Reread the full question and answer here. )

As always, I agree with the Ethicist. I would add that the letter writer’s former patient doesn’t realize that the therapist is actually two different people — the professional and the regular person underneath. Therapists portray their professional selves to their clients. The former client may be disappointed upon meeting the therapist outside of the professional context. Additionally, the feelings she has toward the therapist may be based on transference, and they would need to address that. — Annemarie

I am a clinical psychologist. While the Ethicist’s description of professional ethical boundaries is correct, there is more to the story, and I disagree with his conclusion. A very big question here is why this former patient contacted him after 45 years. That is a question that is best explored and answered within the context of a therapeutic relationship. He would be well- advised to respond in a kind and thoughtful way to convey the clear message that he is not available for ongoing communication, and he should suggest that she consult with another therapist if she feels that would be helpful. — Margaret

In my case, it was the therapist who reached out to me, seeking to establish a friendship several years after our sessions ended. I was surprised, but he shared that he had since experienced a similar personal tragedy to one I had explored with him in sessions. Since it had been several years since we saw each other professionally, I responded. There was never any hint of romantic or sexual interest. Still, as he continued to reach out to me, clearly desiring a friendship, it never felt right to me. It did feel unprofessional, as his knowledge of me was borne out of a relationship meant to be professional, never personal, as warmly as we might have felt during our sessions. I ended up being disappointed in him for seeking out my friendship. — Liam

I am a (semi)retired psychiatrist who has been practicing since 1974. In my opinion, “once a patient, always a patient” is correct. Establishing any type of personal relationship with a former patient could undo progress the patient may have made in treatment, and is a slippery slope toward blatantly unethical behavior. As psychiatrists, our responsibility is to work with patients in confronting and resolving issues that are preventing them from having a reality-based perception of their life. With such an outlook, they are more capable of establishing satisfying relationships with others. An ethical psychiatrist is not in the business of providing such satisfaction to his or her patients. — Roger

I think there is a difference between being friendly and being friends with a former client. As someone who used to attend therapy with a therapist I think dearly of, she made it clear to me that it was OK to send her emails with life updates after our therapeutic relationship ended. But beyond that, I think it would be inappropriate and uncomfortable to pursue a friendship with her, and vice versa, because of the patient-provider relationship that we previously had and the power dynamic that existed between us. The letter writer didn’t share the content of the email his former patient sent to him, but if it’s just a friendly life update, I think it’s fine to write back and thank her for sharing. Beyond that, I feel like it would be unprofessional to meet or pursue a deeper relationship. — Meghan

Kwame Anthony Appiah is The New York Times Magazine’s Ethicist columnist and teaches philosophy at N.Y.U. His books include “Cosmopolitanism,” “The Honor Code” and “The Lies That Bind: Rethinking Identity.” To submit a query: Send an email to [email protected]. More about Kwame Anthony Appiah

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NeurIPS 2024

Conference Dates: (In person) 9 December - 15 December, 2024

Homepage: https://neurips.cc/Conferences/2024/

Call For Papers 

Abstract submission deadline: May 15, 2024

Full paper submission deadline, including technical appendices and supplemental material (all authors must have an OpenReview profile when submitting): May 22, 2024

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The Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024) is an interdisciplinary conference that brings together researchers in machine learning, neuroscience, statistics, optimization, computer vision, natural language processing, life sciences, natural sciences, social sciences, and other adjacent fields. We invite submissions presenting new and original research on topics including but not limited to the following:

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Machine learning is a rapidly evolving field, and so we welcome interdisciplinary submissions that do not fit neatly into existing categories.

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A new future of work: The race to deploy AI and raise skills in Europe and beyond

At a glance.

Amid tightening labor markets and a slowdown in productivity growth, Europe and the United States face shifts in labor demand, spurred by AI and automation. Our updated modeling of the future of work finds that demand for workers in STEM-related, healthcare, and other high-skill professions would rise, while demand for occupations such as office workers, production workers, and customer service representatives would decline. By 2030, in a midpoint adoption scenario, up to 30 percent of current hours worked could be automated, accelerated by generative AI (gen AI). Efforts to achieve net-zero emissions, an aging workforce, and growth in e-commerce, as well as infrastructure and technology spending and overall economic growth, could also shift employment demand.

By 2030, Europe could require up to 12 million occupational transitions, double the prepandemic pace. In the United States, required transitions could reach almost 12 million, in line with the prepandemic norm. Both regions navigated even higher levels of labor market shifts at the height of the COVID-19 period, suggesting that they can handle this scale of future job transitions. The pace of occupational change is broadly similar among countries in Europe, although the specific mix reflects their economic variations.

Businesses will need a major skills upgrade. Demand for technological and social and emotional skills could rise as demand for physical and manual and higher cognitive skills stabilizes. Surveyed executives in Europe and the United States expressed a need not only for advanced IT and data analytics but also for critical thinking, creativity, and teaching and training—skills they report as currently being in short supply. Companies plan to focus on retraining workers, more than hiring or subcontracting, to meet skill needs.

Workers with lower wages face challenges of redeployment as demand reweights toward occupations with higher wages in both Europe and the United States. Occupations with lower wages are likely to see reductions in demand, and workers will need to acquire new skills to transition to better-paying work. If that doesn’t happen, there is a risk of a more polarized labor market, with more higher-wage jobs than workers and too many workers for existing lower-wage jobs.

Choices made today could revive productivity growth while creating better societal outcomes. Embracing the path of accelerated technology adoption with proactive worker redeployment could help Europe achieve an annual productivity growth rate of up to 3 percent through 2030. However, slow adoption would limit that to 0.3 percent, closer to today’s level of productivity growth in Western Europe. Slow worker redeployment would leave millions unable to participate productively in the future of work.

Demand will change for a range of occupations through 2030, including growth in STEM- and healthcare-related occupations, among others

This report focuses on labor markets in nine major economies in the European Union along with the United Kingdom, in comparison with the United States. Technology, including most recently the rise of gen AI, along with other factors, will spur changes in the pattern of labor demand through 2030. Our study, which uses an updated version of the McKinsey Global Institute future of work model, seeks to quantify the occupational transitions that will be required and the changing nature of demand for different types of jobs and skills.

Our methodology

We used methodology consistent with other McKinsey Global Institute reports on the future of work to model trends of job changes at the level of occupations, activities, and skills. For this report, we focused our analysis on the 2022–30 period.

Our model estimates net changes in employment demand by sector and occupation; we also estimate occupational transitions, or the net number of workers that need to change in each type of occupation, based on which occupations face declining demand by 2030 relative to current employment in 2022. We included ten countries in Europe: nine EU members—the Czech Republic, Denmark, France, Germany, Italy, Netherlands, Poland, Spain, and Sweden—and the United Kingdom. For the United States, we build on estimates published in our 2023 report Generative AI and the future of work in America.

We included multiple drivers in our modeling: automation potential, net-zero transition, e-commerce growth, remote work adoption, increases in income, aging populations, technology investments, and infrastructure investments.

Two scenarios are used to bookend the work-automation model: “late” and “early.” For Europe, we modeled a “faster” scenario and a “slower” one. For the faster scenario, we use the midpoint—the arithmetical average between our late and early scenarios. For the slower scenario, we use a “mid late” trajectory, an arithmetical average between a late adoption scenario and the midpoint scenario. For the United States, we use the midpoint scenario, based on our earlier research.

We also estimate the productivity effects of automation, using GDP per full-time-equivalent (FTE) employee as the measure of productivity. We assumed that workers displaced by automation rejoin the workforce at 2022 productivity levels, net of automation, and in line with the expected 2030 occupational mix.

Amid tightening labor markets and a slowdown in productivity growth, Europe and the United States face shifts in labor demand, spurred not only by AI and automation but also by other trends, including efforts to achieve net-zero emissions, an aging population, infrastructure spending, technology investments, and growth in e-commerce, among others (see sidebar, “Our methodology”).

Our analysis finds that demand for occupations such as health professionals and other STEM-related professionals would grow by 17 to 30 percent between 2022 and 2030, (Exhibit 1).

By contrast, demand for workers in food services, production work, customer services, sales, and office support—all of which declined over the 2012–22 period—would continue to decline until 2030. These jobs involve a high share of repetitive tasks, data collection, and elementary data processing—all activities that automated systems can handle efficiently.

Up to 30 percent of hours worked could be automated by 2030, boosted by gen AI, leading to millions of required occupational transitions

By 2030, our analysis finds that about 27 percent of current hours worked in Europe and 30 percent of hours worked in the United States could be automated, accelerated by gen AI. Our model suggests that roughly 20 percent of hours worked could still be automated even without gen AI, implying a significant acceleration.

These trends will play out in labor markets in the form of workers needing to change occupations. By 2030, under the faster adoption scenario we modeled, Europe could require up to 12.0 million occupational transitions, affecting 6.5 percent of current employment. That is double the prepandemic pace (Exhibit 2). Under a slower scenario we modeled for Europe, the number of occupational transitions needed would amount to 8.5 million, affecting 4.6 percent of current employment. In the United States, required transitions could reach almost 12.0 million, affecting 7.5 percent of current employment. Unlike Europe, this magnitude of transitions is broadly in line with the prepandemic norm.

Both regions navigated even higher levels of labor market shifts at the height of the COVID-19 period. While these were abrupt and painful to many, given the forced nature of the shifts, the experience suggests that both regions have the ability to handle this scale of future job transitions.

Businesses will need a major skills upgrade

The occupational transitions noted above herald substantial shifts in workforce skills in a future in which automation and AI are integrated into the workplace (Exhibit 3). Workers use multiple skills to perform a given task, but for the purposes of our quantification, we identified the predominant skill used.

Demand for technological skills could see substantial growth in Europe and in the United States (increases of 25 percent and 29 percent, respectively, in hours worked by 2030 compared to 2022) under our midpoint scenario of automation adoption (which is the faster scenario for Europe).

Demand for social and emotional skills could rise by 11 percent in Europe and by 14 percent in the United States. Underlying this increase is higher demand for roles requiring interpersonal empathy and leadership skills. These skills are crucial in healthcare and managerial roles in an evolving economy that demands greater adaptability and flexibility.

Conversely, demand for work in which basic cognitive skills predominate is expected to decline by 14 percent. Basic cognitive skills are required primarily in office support or customer service roles, which are highly susceptible to being automated by AI. Among work characterized by these basic cognitive skills experiencing significant drops in demand are basic data processing and literacy, numeracy, and communication.

Demand for work in which higher cognitive skills predominate could also decline slightly, according to our analysis. While creativity is expected to remain highly sought after, with a potential increase of 12 percent by 2030, work activities characterized by other advanced cognitive skills such as advanced literacy and writing, along with quantitative and statistical skills, could decline by 19 percent.

Demand for physical and manual skills, on the other hand, could remain roughly level with the present. These skills remain the largest share of workforce skills, representing about 30 percent of total hours worked in 2022. Growth in demand for these skills between 2022 and 2030 could come from the build-out of infrastructure and higher investment in low-emissions sectors, while declines would be in line with continued automation in production work.

Business executives report skills shortages today and expect them to worsen

A survey we conducted of C-suite executives in five countries shows that companies are already grappling with skills challenges, including a skills mismatch, particularly in technological, higher cognitive, and social and emotional skills: about one-third of the more than 1,100 respondents report a shortfall in these critical areas. At the same time, a notable number of executives say they have enough employees with basic cognitive skills and, to a lesser extent, physical and manual skills.

Within technological skills, companies in our survey reported that their most significant shortages are in advanced IT skills and programming, advanced data analysis, and mathematical skills. Among higher cognitive skills, significant shortfalls are seen in critical thinking and problem structuring and in complex information processing. About 40 percent of the executives surveyed pointed to a shortage of workers with these skills, which are needed for working alongside new technologies (Exhibit 4).

Companies see retraining as key to acquiring needed skills and adapting to the new work landscape

Surveyed executives expect significant changes to their workforce skill levels and worry about not finding the right skills by 2030. More than one in four survey respondents said that failing to capture the needed skills could directly harm financial performance and indirectly impede their efforts to leverage the value from AI.

To acquire the skills they need, companies have three main options: retraining, hiring, and contracting workers. Our survey suggests that executives are looking at all three options, with retraining the most widely reported tactic planned to address the skills mismatch: on average, out of companies that mentioned retraining as one of their tactics to address skills mismatch, executives said they would retrain 32 percent of their workforce. The scale of retraining needs varies in degree. For example, respondents in the automotive industry expect 36 percent of their workforce to be retrained, compared with 28 percent in the financial services industry. Out of those who have mentioned hiring or contracting as their tactics to address the skills mismatch, executives surveyed said they would hire an average of 23 percent of their workforce and contract an average of 18 percent.

Occupational transitions will affect high-, medium-, and low-wage workers differently

All ten European countries we examined for this report may see increasing demand for top-earning occupations. By contrast, workers in the two lowest-wage-bracket occupations could be three to five times more likely to have to change occupations compared to the top wage earners, our analysis finds. The disparity is much higher in the United States, where workers in the two lowest-wage-bracket occupations are up to 14 times more likely to face occupational shifts than the highest earners. In Europe, the middle-wage population could be twice as affected by occupational transitions as the same population in United States, representing 7.3 percent of the working population who might face occupational transitions.

Enhancing human capital at the same time as deploying the technology rapidly could boost annual productivity growth

About quantumblack, ai by mckinsey.

QuantumBlack, McKinsey’s AI arm, helps companies transform using the power of technology, technical expertise, and industry experts. With thousands of practitioners at QuantumBlack (data engineers, data scientists, product managers, designers, and software engineers) and McKinsey (industry and domain experts), we are working to solve the world’s most important AI challenges. QuantumBlack Labs is our center of technology development and client innovation, which has been driving cutting-edge advancements and developments in AI through locations across the globe.

Organizations and policy makers have choices to make; the way they approach AI and automation, along with human capital augmentation, will affect economic and societal outcomes.

We have attempted to quantify at a high level the potential effects of different stances to AI deployment on productivity in Europe. Our analysis considers two dimensions. The first is the adoption rate of AI and automation technologies. We consider the faster scenario and the late scenario for technology adoption. Faster adoption would unlock greater productivity growth potential but also, potentially, more short-term labor disruption than the late scenario.

The second dimension we consider is the level of automated worker time that is redeployed into the economy. This represents the ability to redeploy the time gained by automation and productivity gains (for example, new tasks and job creation). This could vary depending on the success of worker training programs and strategies to match demand and supply in labor markets.

We based our analysis on two potential scenarios: either all displaced workers would be able to fully rejoin the economy at a similar productivity level as in 2022 or only some 80 percent of the automated workers’ time will be redeployed into the economy.

Exhibit 5 illustrates the various outcomes in terms of annual productivity growth rate. The top-right quadrant illustrates the highest economy-wide productivity, with an annual productivity growth rate of up to 3.1 percent. It requires fast adoption of technologies as well as full redeployment of displaced workers. The top-left quadrant also demonstrates technology adoption on a fast trajectory and shows a relatively high productivity growth rate (up to 2.5 percent). However, about 6.0 percent of total hours worked (equivalent to 10.2 million people not working) would not be redeployed in the economy. Finally, the two bottom quadrants depict the failure to adopt AI and automation, leading to limited productivity gains and translating into limited labor market disruptions.

Four priorities for companies

The adoption of automation technologies will be decisive in protecting businesses’ competitive advantage in an automation and AI era. To ensure successful deployment at a company level, business leaders can embrace four priorities.

Understand the potential. Leaders need to understand the potential of these technologies, notably including how AI and gen AI can augment and automate work. This includes estimating both the total capacity that these technologies could free up and their impact on role composition and skills requirements. Understanding this allows business leaders to frame their end-to-end strategy and adoption goals with regard to these technologies.

Plan a strategic workforce shift. Once they understand the potential of automation technologies, leaders need to plan the company’s shift toward readiness for the automation and AI era. This requires sizing the workforce and skill needs, based on strategically identified use cases, to assess the potential future talent gap. From this analysis will flow details about the extent of recruitment of new talent, upskilling, or reskilling of the current workforce that is needed, as well as where to redeploy freed capacity to more value-added tasks.

Prioritize people development. To ensure that the right talent is on hand to sustain the company strategy during all transformation phases, leaders could consider strengthening their capabilities to identify, attract, and recruit future AI and gen AI leaders in a tight market. They will also likely need to accelerate the building of AI and gen AI capabilities in the workforce. Nontechnical talent will also need training to adapt to the changing skills environment. Finally, leaders could deploy an HR strategy and operating model to fit the post–gen AI workforce.

Pursue the executive-education journey on automation technologies. Leaders also need to undertake their own education journey on automation technologies to maximize their contributions to their companies during the coming transformation. This includes empowering senior managers to explore automation technologies implications and subsequently role model to others, as well as bringing all company leaders together to create a dedicated road map to drive business and employee value.

AI and the toolbox of advanced new technologies are evolving at a breathtaking pace. For companies and policy makers, these technologies are highly compelling because they promise a range of benefits, including higher productivity, which could lift growth and prosperity. Yet, as this report has sought to illustrate, making full use of the advantages on offer will also require paying attention to the critical element of human capital. In the best-case scenario, workers’ skills will develop and adapt to new technological challenges. Achieving this goal in our new technological age will be highly challenging—but the benefits will be great.

Eric Hazan is a McKinsey senior partner based in Paris; Anu Madgavkar and Michael Chui are McKinsey Global Institute partners based in New Jersey and San Francisco, respectively; Sven Smit is chair of the McKinsey Global Institute and a McKinsey senior partner based in Amsterdam; Dana Maor is a McKinsey senior partner based in Tel Aviv; Gurneet Singh Dandona is an associate partner and a senior expert based in New York; and Roland Huyghues-Despointes is a consultant based in Paris.

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Can Online Music Platforms Be Fair? An Interdisciplinary Research Manifesto

• Open access
• Published: 07 February 2024
• Volume 55 , pages 249–279, ( 2024 )

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• Giuseppe Mazziotti 1 &
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A Publisher Correction to this article was published on 26 February 2024

This article has been updated

In this article we present a manifesto for research into the complex interplay between social media, music streaming services, and their algorithms, which are reshaping the European music industry – a sector that has transitioned from ownership to access-based models. Our focus is to assess whether the current digital economy supports a fair and sustainable development for cultural and creative industries. The manifesto is designed to pave the way for a comprehensive analysis. We begin with the context of our research by briefly examining the de-materialisation of the music industry and the critical role of proprietary algorithms in organising and ranking creative works. We then scrutinise the notion of “fairness” within digital markets, a concept that is attracting increasing policy interest in the EU. We believe that, for “fairness” to be effective, the main inquiry around this concept – especially as regards remuneration of music creators – must be necessarily interdisciplinary. This presupposes collaboration across complementary fields to address gaps and inconsistencies in the understanding of how these platforms influence music creation and consumption and whether these environments and technologies should be regulated. We outline how interdisciplinary expertise (political science, law, economics, and computer science) can enhance the current understanding of “fairness” within Europe’s cultural policies and help address policy challenges. The article details how our research plan will unfold across various disciplinary hubs of a Horizon Europe project ( Fair MusE ) that aims to explore the challenges and opportunities of today’s digital music landscape. The plan culminates in the integration of these hubs’ findings to deliver “key exploitable results”.

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1 Introduction

The exponential growth of social media and streaming services, and the fast-growing influence of their algorithms and data infrastructures, raise questions as to whether today’s digital economy will allow the cultural and creative industries (CCIs), and especially the music ecosystem, to develop in a fair and sustainable way, at least for most authors and performers. The digital revolution has done much more than just simplify content dissemination and enable content production to reach unprecedented scales. Digital technologies have broadened the notion of “creation” itself, which ranges from traditional works of composers, performers, record labels, and broadcasters to new forms of musical and music-based creativity that digital settings, social media, and artificial intelligence (AI) have enabled. These new forms and trends include the streaming of live music events and home-made creations that became even more appealing and diffused due to the COVID-19 health emergency and the ensuing long-term restrictions on the performing arts. In this scenario, the commercial power of a handful of very large tech companies increased significantly. These companies can be identified, at least in part, with the owners of the “very large online platforms” (VLOPs) Footnote 1 under Art. 33 of the DSA and with providers of core platform services according to the notion embodied in the DMA. Footnote 2 The ability of these companies to control access to unprecedented volumes of creative works and, at the same time, creators’ ability to reach and develop potential audiences raises existential questions for Europe’s policymakers and the CCIs, including players such as radio, TV broadcasters, and the market for live performance exploitations.

This paper takes the form of a manifesto to advocate a new, interdisciplinary research approach that can remedy the shortcomings of a purely doctrinal and scientifically segregated (i.e. “silo-like”) analysis of EU cultural and industrial policies in the music sector and of their effective impact in today’s platform- and algorithm-dominated economy. In our view, only a well-designed combination of distinct and complementary disciplines can test methodologically and verify empirically whether the EU’s policy changes in copyright law and recent EU regulations (Digital Services Act – DSA – and Digital Markets Act – DMA) seeking to curb the exceptional power of VLOPs are justified and suitable for today’s internet. To this end, we authored a research proposal and built an EU-wide interdisciplinary group of academics and industry partners whose consortium – Fair MusE Footnote 3 – received funding from the EC/REA’s Horizon Europe program. The group’s principal investigators are experts in the fields of law, economics, political science, and computer science and have a consolidated leadership in developing projects of international relevance and solid connections with policymakers and industry.

The predominantly academic character of this consortium Footnote 4 aims at guaranteeing the highest quality and independence of the proposed research. The consortium composition seeks to prevent conflicts of interests which would inevitably arise in our view if, due to the project’s mission, the consortium incorporated industry partners (such as a major record publisher or label, an online music service provider, or a social media platform owner) that would pursue their own corporate interests. This could hinder, or even distort, the results of the empirical research concerning data and confidential information Fair MusE has envisaged. To prevent this risk while still being able to engage in “co-creation” of tools for policymakers and the music industry together with CCIs, our consortium incorporates industry partners which have an interest in promoting fairness in music ecosystems: (i) an Italian composers’ collecting society (SIAE), which is broadly representative of Italian composers and whose repertoire is strong at the local level but not mainstream at the international level; Footnote 5 and (ii) a UK-based company (Verifi Media Ltd) that is currently leading the market development of rights data management services for the music industry, including data collaboration and sharing, which are a prerequisite for market transparency for both creators and exploiters of digital music. Footnote 6

Our manifesto is based on Fair MusE’s main research proposal and puts forward a novel approach to address the European idea of a “fair” digital society and of fair digital markets in the music sector in an extensive and integrated manner. Such a necessity is even more compelling at the European level if we consider that the notion of “fairness” is currently being used in several policy areas. Footnote 7 Considering that fairness is designed to support cultural creation in today’s fast-changing, very broad, and increasingly AI-dominated music ecosystems, independent research should give this concept a more tangible and measurable dimension. Our manifesto and its potential outcomes aim at pursuing this goal and making policymakers, stakeholders, and the general public more aware of the risks that creators’ lack of appropriate remuneration as well as platforms’ algorithm-based and non-transparent exploitations of creative works pose to music’s sustainability and diversity.

The manifesto is organised as follows. Section 2 briefly summarises how the music industry has progressively de-materialised over the past three decades and gone from ownership-based to access-centred business models where streaming services and social media platforms organise and rank sound recordings on the grounds of their (secret) algorithms. Section 3 lists complementary disciplines and methods that are necessary to perform effective and independent research activities focused on whether music platforms can function fairly, especially for music creators. This section identifies gaps in the literature and shows how interdisciplinary research can go beyond the state of the art and help resolve persisting policy dilemmas in this field. Section 4 describes the main contents and purposes of our manifesto while drawing on the emerging notion of fairness in EU music policymaking and other policy fields. Section 5 details how we see our ideas being put into practice in Fair MusE’s research proposal and concrete set of activities.

2 Evolution of the Music Industry and Its Current Dependence on Platforms

The music industry, more than other sectors, has gone through radical changes in the past two decades. These have been even more difficult to face because of the extreme fragmentation of the rights, business interests, and artistic prerogatives that characterise the related creative communities. When the internet first emerged in the mid-1990s, the end-to-end architecture of this new medium and the fast development of file-sharing software enabled internet users to access and exchange large amounts of recorded music without intermediation. Free and uncompensated file sharing threatened the survival of the music industry for almost a decade, given that it had the potential to replace physical formats like CDs, which were the core business of the industry. Footnote 8 Since the early 2000s, proprietary online platforms have dramatically changed content distribution models and made music materials ubiquitous in the online environment. Although unauthorised file-sharing continued, becoming even more efficient and sophisticated, an unstoppable evolution of the internet infrastructure in terms of bandwidth and connectivity enabled companies to launch on-demand music stores, such as iTunes, which Apple released in 2001. iTunes was the first service that made digital music marketable by successfully creating its own ecosystem based on proprietary technologies for computers and portable devices. Streaming services like Spotify and Deezer as well as social media platforms like YouTube emerged at a later stage, which consolidated both a trajectory of music consumption from an ownership to an access model as well as a process of online re-intermediation for the whole internet and, even more so, for digital music distribution. This platform-centred environment has allowed music right-holders to start licensing their works and earn remuneration from the technology companies that exploited their music. Despite this evolution, music right-holders’ communities claim not only that the value of their works has been disrupted by a platform-dominated economy but also that a “value gap” exists between the remuneration they earn from music streaming services and social media platforms. Footnote 9

Our interdisciplinary research agenda seeks to understand and illustrate, in an autonomous and evidence-based way, the consequences that the various business models deployed by the largest digital music platforms have had as far as music production, distribution, and consumption processes are concerned. These complex environments are deeply influencing the economic and social value of this art form, in ways which are often contradictory from a public policy perspective. On the one hand, platforms have effectively enabled new forms of music production and home-made creations that empower amateur, early career, or disenfranchised categories of authors (“professionalising amateurs”) to gain online exposure and eventually establish themselves as music professionals. Footnote 10 On the other hand, these algorithm-dominated businesses seem to have induced a significant impoverishment of creators, especially those of niche or marginal repertoires that are penalised by the logic of filter bubbles and recommender systems.

The above-mentioned scenario has led to significant reforms of legal and regulatory frameworks that aim to govern and shape European music ecosystems. The most significant among these adaptations are embodied in Directive 2019/790: Footnote 11

This directive seeks to protect the commercial value of copyright works – in particular recorded music – by making providers of online sharing content services directly liable for works their users make available. Footnote 12 This policy change represents a turn away from the legal principle of platform neutrality that EU lawmakers maintained for nearly two decades to stimulate the growth of a robust internet infrastructure. In reversing this principle, the legal provision aimed at obliging social media companies to obtain licences and to implement content identification technologies that can either restrict access to unauthorised works or help copyright holders to be remunerated for online exploitation of their works.

A second, potentially very impactful change is condensed into Chapter 3 of the directive, where the law codifies a principle of fair and proportionate remuneration for authors and performers, in particular with regard to online music exploitations, Footnote 13 and a right to receive – on a regular basis – timely, accurate, relevant, and comprehensive information on modes of exploitation of their works, direct and indirect revenues generated, as well as any remuneration due. Footnote 14

We believe that both these policy changes constitute a turning point or even a “big bang” in the European history of copyright and artists’ rights, whose real effects are yet to be evaluated in a non-doctrinal and evidence-based way. This has not happened yet because of the very slow transposition of these provisions into national laws and an approach to academic research on these reforms that we find incomplete, too abstract and ideological, and discipline-segregated (“silo-like”).

3 Advancing Complementary Disciplinary Expertise to Go Beyond the State of the Art

Our research presupposes the identification of disciplines that can eventually enable independent scholars to fully understand the consequences of market-driven and legislative changes in Europe’s music ecosystem, going beyond the state of the art in measuring and enhancing the impact of the main EU policymaking initiatives in this field. While the music industry has been analysed from an economic perspective, Footnote 15 we believe that these analyses should be strongly connected to political, legal, and technical investigations and a thorough empirical exploration of the societal impact of music platforms on European music creators and audiences. In the following subsections we seek to identify gaps in the literature and illustrate how research can produce new knowledge to the benefit of policymakers, stakeholders, and society at large.

3.1 Politics: The EU as a Policymaker in the Music Industry

Despite a series of thoughtful studies on EU cultural-media policies, Footnote 16 there has so far been no comprehensive attempt to examine and critically assess the ways in which EU policy and law have sought to cope with the notion and the goal of fairness in the music sector, the values underpinning the policy instruments introduced (market vs. non-market values), and the objectives pursued. We believe that the first pillar of an effective research agenda in this field should be a comprehensive policy analysis of different EU initiatives that relate to the music sector. We need such an exhaustive analysis to understand the origin, nature, breadth, and degree of policy changes towards the governance of online platforms in Europe and the implications for the music ecosystem. This endeavour shall consist in scrutinising several policy instruments, proposals, and reports, including key documents related to “Music Moves Europe”, that the EU has issued in the past three decades. Footnote 17

Our analysis will focus predominantly on three issues that have dominated debates on online platforms and EU music governance in the past few years: (i) the availability and prominence of local and national music content online; (ii) the rights for creators in relation to the use of their music works by online service providers; and (iii) a fair and proportionate remuneration of music creators. Our team will engage in a historical analysis covering a span of 30 years of EU policy initiatives in this sector to understand the nature and breadth of policy changes towards the governance of music streaming and social media platforms, including the latest tweaks that specifically regard fairness and transparency. This analysis will also help us address the way EU governance rules seek to promote fairness in an economy where platforms’ dominance was exacerbated by the COVID-19 pandemic. We believe that an in-depth understanding of these changes is essential for policymakers as well as key digital industry players and music associations to assess the pros and cons of an increasingly pervasive dimension of EU law where copyright, contract law, and various forms of platform regulation are used to govern the extended landscape of business models and music professionals that characterises the platform economy. This unprecedented policy analysis can produce, in our view, new knowledge on the impact of online platforms and of phenomena such as the COVID-19 pandemic on music production and dissemination and thus contribute to finding solutions with a clear potential to bolster fairness.

3.2 Law: Copyright, Contract Law, and Platform Liability

Despite the adoption of the DSA and its broad attempt to introduce new obligations for VLOPs, the most important form of regulation aimed at helping music right-holders exercise their rights in the social media landscape is Art. 17 of the 2019 Copyright Directive. Footnote 18 This provision aims at setting a new standard of copyright liability applicable to social media platforms and at excluding the (previously uncertain) application of liability exemptions embodied in Directive 2000/31 (e-Commerce Directive). Footnote 19 Since it was included (as Art. 13) in the EU Commission’s directive proposal in September 2016, this provision has been the target of an endless number of academic articles, studies, parliament interrogations, open letters, popular petitions, and other initiatives that aimed at flagging the “negatives” of the complex legal mechanism it incorporates, especially for the protection of freedom of expression and “internet freedom”. Footnote 20 The volume and the strength of this critical movement increased, and became even more apparent, as soon as the EU Member States started transposing this provision in a rather inhomogeneous, scattered, and (mostly) untimely manner. Footnote 21 Such a broadly shared and vehement attack on this provision found its point of sublimation in the appeal brought by the Republic of Poland against Art. 17 before the European Court of Justice (ECJ), which the Court eventually rejected. Footnote 22

Our research agenda, while duly considering the controversial aspects of this provision, as reflected in an exceptionally abundant literature, aims mostly at identifying its “positives”. We believe that only a fairness-centred reading and an evidence-based analysis of Art. 17 and its national implementations can tell whether this legislative reform strikes a suitable balance between antagonistic interests. A literature review shows that, from a constitutional perspective, many European legal scholars tend to place copyright and the rights of authors at a level that is lower than that of other fundamental rights. Several scholars write as if internet users’ freedom of expression and the tech companies’ freedom to run their online businesses should systematically prevail over the authors’ expectation to enforce their rights and to receive fair remuneration for the exploitations of their work. Footnote 23 Despite the relevance of these remarks, this conclusion cannot be justified on the grounds of the European human rights framework if we consider that even the European Court of Human Rights (ECtHR), in several judgments, held that copyright, as a form of “property”, prevailed over other fundamental rights. Footnote 24 This conclusion is even clearer and stronger under EU law, considering the constitutionalisation of the EU Charter of Fundamental Rights. As recently held by the ECJ on the grounds of the Charter, the complex provision of Art. 17 of the 2019 Copyright Directive can be viewed as a proportionate and legitimate attempt to ensure a fair balance between the protection of users’ and online intermediaries’ interests, on the one hand, and creators’ rights on the other. Footnote 25 In the social media industry, the ECJ’s reasoning in Poland v. Parliament and Council emphasised that, although not inviolable and absolute, the right to intellectual property embodied in Art. 17(2) of the EU Charter on Fundamental Rights is a human right whose high level of protection justifies the complex regulation embodied in Art. 17 of the 2019 Copyright Directive and supports its adoption and EU-wide enforcement. Footnote 26 This opinion is perfectly consistent with the continental European approach to copyright and authors’ rights as personality rights and human rights that give rise to moral and economic prerogatives. Footnote 27

Currently, the implementation of a principle of “fair balance” based on the EU Charter of Fundamental Rights clearly shows that (i) the protection of authors’ rights can prevail over other fundamental rights, and (ii) the resolution of disputes in this field, especially in online environments, requires the ECJ to engage in a case-by-case assessment of the various interests at stake. Footnote 28 Our research seeks to provide more than just a doctrinal analysis of the effective impact of the 2019 Copyright Directive in the European music sector. In doing so, we intend to embrace an evidence-based and neutral approach to Art. 17, which only a minority of European scholars seem to have pursued, at least in the literature available in English. Footnote 29 To fill this gap, we will involve stakeholders and experts in empirical investigations to ascertain whether platform obligations, on the one hand, and copyright exceptions and the remedies embodied in Art. 17 to protect media and artistic freedoms, on the other hand, are being effectively implemented across EU Member States. Moreover, to assess more objectively the impact of content filtering measures, we will scrutinise music licensing practices, the use of content-recognition technologies, and other forms of content moderation before and after the entry into force of Art. 17’s national transpositions. This is relevant, in our view, also to understand whether these practices are well-established policies of social media services even in jurisdictions where a provision like Art. 17 and a brand-new legal infrastructure such as the DSA do not exist.

An equally relevant research gap in legal scholarship exists regarding the interplay of Art. 17 with other principles, rights, and obligations embodied in Chapter 3 of the 2019 Copyright Directive. Our research project assumes that, without empirical investigations, it is impossible to assess the effects of these joint measures on the businesses of legacy music producers and new generations of music creators. As things stand, the above-mentioned legal principles of fairness, proportionate remuneration, and transparency are likely to remain empty promises without the development of a new, data-driven approach to creators’ rights. This approach can only be based on the availability of large volumes of data enabling music creators, their representatives, and online exploiters to negotiate and conclude licensing agreements in a smooth, nuanced, machine-readable, transparent, and thus fair manner. Footnote 30 Our research proposal assumes that, in data-analytics businesses like digital platforms, even subscription-based services that choose and curate their repertoires (negotiating and paying royalties to creators) cannot ensure fair and proportionate remuneration without using reliable, standardised, and unequivocal copyright ownership and management information coming from the music sector. Footnote 31 The research we advocate in this field goes beyond the state of the art by providing a cross-country empirical analysis of the impact of recent copyright and contract law provisions embodied in the 2019 Copyright Directive and, at an earlier stage, Directive 2014/26 on the collective management of copyright on the music industry, broadly defined. Footnote 32 Our research includes an evaluation of how EU competition law and EU regulations (including the DSA, DMA, and upcoming legislation such as the EU Artificial Intelligence Act Footnote 33 and the EU Data Act Footnote 34 ) can apply and have an impact in the domain of online music platforms. This will allow us not only to produce evidence-based policy recommendations, but also to formulate a law-data-and-technology concept – built on the grounds of “co-creation” with stakeholders – to identify and rank solutions to the problem of information asymmetry across online platforms in Europe.

3.3 Economics and Business: Music Professionals and Value Networks

The music industry has been at the forefront of CCIs when it comes to the impact of technological advancements and related business model innovations. Currently, streaming platforms and social media are dominating the market, relying on their crucial position as intermediaries Footnote 35 and benefiting from winner-takes-all effects. Footnote 36 Their new business models, favouring access over ownership Footnote 37 and relying on the availability of vast amounts of (real-time) data, are accused of altering the value of content, particularly music. The music industry and its business models have constantly evolved with digitalisation and the growing domination of platforms. Footnote 38 Economists can contribute to interdisciplinary research by integrating the latest advancements in their analysis of value networks, of music professionals’ perspectives, and of innovative business models and by offering a longitudinal perspective on ecosystems, extensive surveys, and the use of quick-scan analysis to map large numbers of companies’ business models. Footnote 39 This will notably allow the integration of the role of “professionalising amateurs”, Footnote 40 a new category of content creators who act as YouTube, TikTok, or other social media’s partners, with growing economic and cultural relevance. After YouTube’s launch of its creator partnerships and programmatic advertising in 2006, these social media platforms started signing creators for the purpose of maximising value from their content and communities. More generally, the economic and business analysis of the music industry will consider the role played by data. A major disruption emerged from the availability of vast amounts of (real-time) data for music platforms. By translating data on user’s music consumption into relevant metrics, some authors argue, the business model of the industry was reshaped from music as a product to music as a service. Footnote 41 This is the case for services relying on advertising (content-sharing services like YouTube and Spotify’s free service) since data allow for the personalisation of advertising. This is, however, also the case with licensed services. For example, Spotify’s freemium model has been strongly supported by the platform’s focus on personalised content, which has been key in converting users to premium subscriptions. Footnote 42 Curated user-specific playlists are part of their product offering and perceived value. Footnote 43

The economic analysis we advocate addresses the notion of fairness notably in relation to value networks. While there is an increasing policy interest in ensuring that music streaming platforms are fair, there is a research gap regarding the industry’s and music professionals’ perspectives on fairness in the music platform market. Footnote 44 Since online platforms have become major enablers of music content flow, with unparalleled gatekeeping powers, Footnote 45 the remuneration of creators deeply depends on monetisation practices of platforms and on the ways through which algorithms expose information and cultural content. Footnote 46 However, to properly define this notion, there is an empirical gap regarding the industry’s and music professionals’ understandings of fairness in the music platform economy at both the European and national levels. Footnote 47 This task is even more complex if we consider that the impact of COVID-19 on culture and the performing arts has led to re-evaluations of the power of these platforms, paving the way for in-depth research into how industry representatives from the tech and music sectors conceptualise the fairness of music streaming platforms and social media. Footnote 48 The dramatic consequences of the recent pandemic for the performing arts encouraged several countries to start public inquiries into the power of global platforms, whose consequences are yet to be seen. Footnote 49

3.4 Computer Science: Influence of Algorithms on Music Consumption

Despite being presented as easing consumer choice, Footnote 50 platforms’ recommender algorithms are accused of lacking transparency, Footnote 51 threatening the exposure of content diversity and thereby challenging democracies Footnote 52 as well as violating consumers’ rights and citizens’ freedom of expression. Footnote 53 Algorithms have been accused of bias, Footnote 54 reinforcing discrimination in the real world, notably linked to race and gender, Footnote 55 and further increasing the popularity of superstars, blockbusters, and best-sellers at the expense of minority perspectives, local content, and emerging artists. Footnote 56 Our research project will highlight the effective influence of algorithms and aim to understand the way algorithms are being designed and implemented by different platforms. Footnote 57 Data are part of the algorithmic systems (especially recommender systems) that build this crucial personalisation process. Technological and economic developments have led to the availability of overwhelming quantities of digital content, notably music. Footnote 58 While some physical limitations have disappeared (for instance: space for storing, time for scheduling), others remain, notably users’ attention and what can be displayed to users (for instance: what a Spotify or YouTube user sees when connecting to the platform). Because of “overchoice”, Footnote 59 item selection can become cumbersome and complicated. Footnote 60 This makes it crucial, especially for media content providers, to incorporate algorithms that allow for a flexible and immediate response and adjustment to personal preferences of consumers. Such algorithms automatically filter, rank, and recommend content. Footnote 61 They influence the display or recommendation of content. Hence, algorithms are not neutral, and they raise questions as to how they are designed and implemented, who decides such matters, and on which basis. Beyond platform providers, all stakeholders in the music industry develop strategies and business models to cope with algorithms and adapt them to their own objectives.

Our research aims to produce new knowledge on the way platforms are affecting music diversity across the consortium members’ countries. In extending the work by Snickars and Mähler to detect and map patterns in algorithmic auditing by Spotify’s recommendation service, Footnote 62 we will account for a shortcoming of their work: access to data. Instead of using fictitious, stereotypical bots acting as users, we believe that this research would be more meaningful and fit for its purpose with the recruitment of a sufficiently broad and diverse number of real users (for instance: +1000). These users can donate their playlist data on the grounds of their right to access personal data collected and stored by streaming services and social media companies under Art. 20 of the General Data Protection Regulation (GDPR). Footnote 63 Although the recruitment of users as personal data donors can be difficult, their involvement can be spurred by a data donation campaign across EU countries to fund symbolic or little monetary rewards, so that users have both a financial and an ethical motivation to participate.

User data are very useful for measuring the influence of algorithms on music consumption because patterns in personal playlists can be compared against one another and with curated playlists obtained from several radio broadcast channels in each of the countries where the investigation takes place. Moreover, in-depth qualitative interviews on music habits, perception of bias, diversity, and serendipity with 100 users can add a qualitative dimension to the interpretation of the playlist data. An important contribution here can be the development of fairness indicators for online platforms’ algorithmic systems based on the analysis of the data collected. To do this analysis, Fair MusE’s data scientists can rely on the use of Human-Num Footnote 64 and Dataiku, Footnote 65 a free software platform to analyse machine-learning algorithms, predictive models, and big data. Indeed, with the data and related statistics, this research can lead to an in-depth data analysis of the way platforms and their algorithms function and influence consumers. With that input, this new research can go further than previous research Footnote 66 by addressing the concept of fairness in a broader way through the development of indicators related to several dimensions.

4 Our Ethos

Disciplinary expertise is core to our work; its interdisciplinary deployment is what makes our research and its empirical investigations meaningful and promising. We believe that to address a multi-faceted concept such as fairness and to use it as an effective and desirable policy and legal instrument in the music sector, the approach shall necessarily be interdisciplinary. New criteria, methodologies, and tools are required.

4.1 The Concept of “Fairness” and Its Special Function in the CCIs

Recent developments in EU law and policymaking clearly show a strong and fast-growing policy interest in the notion of “fairness” in digital markets and ecosystems. Although this notion has various, conflicting facets, EU policy and legislative initiatives through which the European Commission is currently exploring the function of “fairness” clearly aim to promote awareness of how certain structural factors can radically reduce economic output and social welfare in several industries. Footnote 67 Especially in the CCIs, the principle of fairness is expected to reduce financial losses for content creators, whose work is significant not only in terms of economic growth but also in terms of the sustainability of Europe’s cultural and linguistic diversity. Footnote 68 From this angle, the music sector is exceptionally relevant and complex considering its vastness as a cultural and commercial phenomenon and the fact that music is created and enjoyed everywhere, including low-income areas and communities where more expensive and complex types of creative works cannot be produced.

Our research seeks to shed light on the economic, cultural, societal, and technical context of EU music ecosystems, where a great variety of composers, performers, record labels, and platform artists target very different audiences in terms of size and geographical scope without knowing how the main digital music gatekeepers treat, promote, and commercially exploit their works. In this regard, the notion of fairness stands not only as a prerequisite for the pursuit of goals such as sustainability and competitiveness of an entire industry but also as a guarantee of consistency and compliance with the EU’s constitutional obligation to preserve and promote the cultural diversity of artistic productions. An important assumption of our research agenda is that EU lawmakers believe that a genuinely diverse music ecosystem can thrive only on the grounds of contractual and economic fairness. This presupposes much greater transparency in collective rights management, data collection, and proportionate remuneration of individual authors and performers. Yet these values, which have been recently embodied in EU legislative measures, are far from materialising in either market realities or in the day-to-day activities of music creators and their commercial and cultural partners.

4.2 Interdisciplinary Effort to Elaborate New Criteria, Methodologies and Tools

Our investigation entails considering a broad variety of online and offline environments where music professionals are involved, and assessing contemporary uncertainties around music’s economic and societal value and how they challenge creators’ opportunities to thrive and make a living. We believe that, notwithstanding the exceptional challenges that platformisation poses to a more transparent, competitive, and sustainable music sector in Europe, the current state of digitalisation holds the potential to help a great variety of music creators gain recognition beyond local or national borders and to overcome physical limitations. To investigate the impact of platforms on CCIs, a truly interdisciplinary team and approach are needed to connect media production, dissemination, and use on the one hand, and the legal conditions that are expected to achieve public policy goals on the other. Where our research seeks to innovate the most concerns tackling “fairness” from a conceptual perspective, considering it as a complex concept that requires interdisciplinarity and the analysis of several stakeholders’ perspectives and points of view. In a digital media economy where the largest gatekeepers are data-analytics businesses, appealing content such as music (in both audio and audiovisual formats) is used to attract and keep users active on the gatekeepers’ platforms for as long as possible.

Our approach to the notion of fairness from policy, legal, economic, and technical perspectives considers the various challenges raised by the advent and domination of platforms such as YouTube, Spotify, and, more recently, TikTok. Our research project is designed to unveil how today’s music industry can significantly improve and evolve in terms of transparency and access to relevant data. So far, the digital music sector has been dominated by trade secrecy, which has made it very difficult for policymakers to intervene by developing appropriate policy measures. Footnote 69 Our assumption is that greater transparency in the music sector and broader societal participation can help fight some phenomena that systematically penalise the majority of performing artists, music composers, and content producers. These phenomena include the implementation of unfair algorithmic systems and a race to the bottom that leads to the degradation of the commercial value of professionally created music and unfair remuneration. Our research also assumes that there is an exceptionally complex problem of data asymmetry across different stakeholders in the value chains, insofar as online platforms treat data about artists’ and content producers’ compensation and modes of content supply, exploitation, and consumption as a trade secret, claiming they need to protect data from industrial competition. The restricted access to data raises major issues in terms of accountability and of establishing a level playing field in the music sector. Lack of transparency also prevents the development of policy measures to promote fairness and diversity in a post-COVID-19 context.

In Fair MusE, we aim to investigate whether and how platforms have effectively enabled new forms of music production and home-made creations that empower amateur, early career, or disenfranchised categories of authors (“professionalising amateurs”) to gain online exposure, build and curate new audiences, and eventually become well-established music professionals. Footnote 70 At the same time, this type of analysis will enable the consortium to assess whether content platforms have induced a significant impoverishment of creators of niche or marginal repertoires that seem to be penalised by the logic and functioning of algorithms. Footnote 71

4.3 Our Agenda’s Major Obstacles

In designing our research project and building on the experience of the consortium partners, we have tried to identify potential challenges, the biggest of which is certainly the secrecy of the data our research is expected to collect and draw upon. Our project deals with issues that are very sensitive – commercially and technically – for major economic and political stakeholders at the European and global levels. We are aware of the difficulties this might raise, especially when liaising with the tech companies that own very large platforms and music services. For this reason, our research plan relies on multiple data collection sources and seeks to take advantage of duties of data disclosure that, under certain conditions, EU law imposes on data controllers and processors.

Another difficulty for research dealing with exceptionally large corporate interests such as those that exist in the music sector and, even more so, in the tech industry is that of developing normative recommendations on the EU policy and legal frameworks towards creators, business strategies, or large media environments while facing the risk of capture and lack of neutrality, which could weigh upon each research or communication initiative. Research that takes copyright and creators’ rights as one of its main pillars is subject to a lot of – not necessarily justified – criticism. We know that scientists cannot avoid being drawn into the controversies they are investigating. Footnote 72 In any case, while acknowledging that it can be difficult, especially for social scientists, to ensure neutrality and objectivity when investigating issues that touch upon their values, groups, and cultures, Footnote 73 our objective is to take a balanced approach that relies on critical thinking without ever transforming it into activism.

Another set of challenges comes from the strongly interdisciplinary nature of our research. Public research funding agencies promote and identify interdisciplinarity, but organisational constraints can restrict their capacity to fully embrace novel ways of interdisciplinary collaboration and investigation. Footnote 74 More generally, researchers from different disciplines and different countries work in different contexts, share different objectives, and may simply differ in terms of vocabulary used. Regarding the context, Friedman argues that institutional structures and funding patterns (among other things) make interdisciplinary research difficult. Footnote 75 One could simply add that researchers working in the social sciences in labs or under remote working arrangements (by necessity or by choice) have a totally different experience from their fellows working in biological labs. Moreover, different objectives can be illustrated by the fact that while there are “few more familiar aphorisms in the academic community than ‘publish or perish’”, Footnote 76 the length, the type of outlet (e.g. journal vs. conference proceedings or monographs), the usual number of authors, etc. can vary greatly from one discipline to another. As regards different vocabularies, they are at the core of our work on the multi-faceted notion of fairness. More generally, this challenge relates to the fact that sector-specific differences in methodologies can quickly emerge during interdisciplinary research efforts. Footnote 77 Rogers et al. even suggest that interdisciplinary research can be difficult to achieve due to incommensurable positions adopted by different disciplines. Footnote 78 Cultural differences – as one may find in large European research projects – may add to the difficulty to understand each other. Arguably, some of the interdisciplinary collaborations envisaged in Fair MusE are more common than others (for instance: between law and economics), but our mix is more peculiar. Finally, one challenge could be that interdisciplinary research potentially detracts from researchers’ expertise. While learning from others, researchers may end up spending less time developing their disciplinary expertise. This is largely because interdisciplinary research involves negotiating conflicts. Footnote 79 Sanz-Menéndez therefore finds that interdisciplinary research can lead to both specialisation and fragmentation, depending on the research area. Footnote 80

5 Putting Our Research Agenda into Practice

From a methodological perspective, we believe that a two-phase structure can allow us to pursue our research agenda and put our idea of integrating different disciplinary elements into practice.

5.1 Phase 1

Phase 1 (M1–M24, where “M” stands for “Month”) is designed essentially as a two-year mapping exercise in which four research hubs (which include industry partners) will split into two groups: (i) Law and Political Science, on the one hand, and (ii) Economics and Computer/Data Science on the other. The former focuses on the role of EU regulation, assessing the impact of new or recent policy or lawmaking initiatives targeting online platforms in the existing law and policy scenario (as detailed in Section 5.1.1 ). The latter analyses the complexities of music platforms from the perspectives of music professionals and their business models (see Section 5.1.2 ) and of consumers, where our computer scientists analyse the influence of algorithms on music diversity (Section 5.1.3 ).

5.1.1 Assessing the Role of Regulation

A. Analysis of the normative and policy framework

Our project explores, among others, the domain of music policy and lawmaking through an in-depth critical analysis of EU instruments, reports, and proposals. Footnote 81 The consortium will pay special attention to the 2019 Copyright Directive and to the overarching framework for the EU Commission’s actions in support of the European music sector: “Music Moves Europe”. Footnote 82 Both instruments are exceptionally important pillars of the EU music sector policy, seeking to address key concerns of this industry and professionals in terms of financial aid, intellectual property rights regulation and subsidies. Considering that fairness has been a key driver for rethinking the sector-specific objectives of EU policy initiatives, Footnote 83 it is crucial for our project to explore the role of policymaking over the past few decades and to understand the evolution of this field and how (and when) “fairness” became a priority.

B. Music creators’ rights under EU law

This part of our work focuses mainly on the rights and other prerogatives originating from the implementation of Directive 2001/29 (the so-called “Information Society” Directive), Footnote 84 the 2014 Collective Rights Management (CRM) Directive, and the 2019 Copyright Directive. We will investigate the practical implications of authors’ and performers’ rights for transparency, fair remuneration, and contractual adjustments (and, possibly, revocation) of their copyright transfers, as laid down in Chapter 3 of the 2019 Copyright Directive. This will be done by analysing the standard “Terms of Service” of each of the aforementioned platforms because they play an essential function from a copyright point of view, granting social media companies a free, global, perpetual, and non-exclusive licence which covers the original work each user-creator uploads. This analytical exercise will have long-term utility, as the DSA imposes more stringent obligations on VLOPs. Footnote 85

C. Copyright liability of social media platforms

This section focuses on the scope and implications of Art. 17 of the 2019 Copyright Directive and of its national transpositions. Footnote 86 We will verify how social media companies seek to obtain licences for all works uploaded by their users and how they eventually restrict access to unauthorised works without infringing on users’ fundamental rights and freedoms. For this task, academics and experts from the consortium’s industry partners, authors’ collecting societies, and music right-holders’ representatives who are members of Fair MusE’s Advisory Board will cooperate closely. Footnote 87

D. Collective rights management in Europe

One of our research assumptions is that the global reach of social media and their multi-territorial distribution of music has been at odds with collective rights management, which has traditionally been fragmented from a territorial perspective, ultimately on the grounds of copyright’s territoriality. Footnote 88 Fair MusE aims to analyse the governance and licensing practices of EU collecting societies, especially for digital uses, as a result of the implementations of the CRM Directive. This analysis is essential to evaluate whether EU law has paved the way for an adequate music metadata infrastructure and the emergence of music data collection standards. Footnote 89 From a music licensing perspective, our main goal is that of ascertaining whether the EU has succeeded in reducing the very high transaction costs that, until the adoption of this directive in 2014, made fair remuneration of various music right-holders very difficult if not impossible. Footnote 90

E. EU competition law

We believe that traditional competition law remedies and the European Commission’s investigations in this field have a significant role to play in targeting potentially anticompetitive practices of dominant music platforms and social media. Footnote 91 This work includes a comparative analysis of the US and EU legal and music market scenarios. For several reasons, US federal antitrust law seems unfit (at least until recently) to remedy the extreme corporate power that the largest platform owners have acquired. Footnote 92 This situation sharply contrasts with that of the EU, where competition law has been widely used against tech companies’ abuses of their dominant position and where policymakers are trying to prevent these abuses through ex ante regulation.

F. Platform regulation and soft law instruments

Fair MusE’s team will consider the interplay between copyright-specific rules in the 2019 Copyright Directive and general obligations of digital platforms arising from regulations such as the DSA and the DMA. Considering that some of the largest online music platforms qualify, under the above-mentioned regulations, as “very large online platforms” and/or “gatekeepers”, we will map and evaluate how data access rights and protection mechanisms enshrined in these regulations impact on music right-holders’ effective participation and business on platforms. This work presupposes an analysis of automated decision-making procedures and music platforms’ content moderation policies, also to understand how many of these activities rely on standardisation, certification procedures, or human review. Our analysis includes soft law instruments, such as codes of conduct and best practices, which might prove essential to promote fairness towards music creators by enhancing data transparency and facilitating fair and proportionate remuneration.

5.1.2 Platforms, Business Models, and Professionals in the Music Industry

A. From value networks in the music industry to new music ecosystems

Our research project analyses evolutions in the music industry considering the implications of dematerialisation, of the dominance of platforms and their increasing reliance on algorithmic systems to filter and recommend content. To do so, based on a methodology applied in previous research, Footnote 93 we will map “value networks” and the inter-relations between actors. To this end, our researchers will identify: (i) the value chains and related activities; (ii) the different stages in the value chains that compose the value networks (including content creation, content production, distribution and placement, support environment, and support industries); (iii) the different actors (both generic names and actual examples of key players) in a process of stakeholder mapping. At the same time, our researchers will analyse relations between the different actors and possible schematic relations with other value networks, mapping inter-relations among, and multi-directional flows of value between, the actors and the process of value creation.

Our research will go beyond the deployment of a “value network” analysis by incorporating business perspectives that are targeted at platform-centred and platform-led networks and ecosystems. The added value of also applying “ecosystem” theories Footnote 94 consists in being able to address a wider range of factors (including regulation, music education, live performances, etc.) that determine how value is being created in the music industry.

The above-mentioned analysis will allow us to observe the impact of online music platforms beyond online streaming consumption. This impact is primarily in the online realm, between uses on different platforms (for instance: how the use of a track excerpt on TikTok can lead to an increase in this track’s exposure on streaming platforms), but also in the interactions between online and more traditional offline uses, such as the cross-effects between live performances and online consumption. Our analysis will finally address fairness from an economic perspective, especially in relation to the “value gap” debates, and more generally issues of creators’ remuneration, Footnote 95 in close connection with the project’s legal analysis (see Section 5.1.1 . supra ).

B. Conflictual and consensual aspects of fairness that digital industry and music professionals consider relevant for platforms

Our project will investigate what “fairness” actually is, not only for music professionals but also for the online platform providers themselves. At the European level, the focus will be on six key European associations: DIGITALEUROPE, DOT Europe, European live music association, European Music Council, European Composer and Songwriter Alliance, and IMPALA. Footnote 96 Data collection will draw on desk research (notably grey literature documents coming from the six associations) and will further be gathered by conducting semi-structured interviews.

At the Member State level, the goal is to explore (i) whether fairness is related to the remuneration of music composers and the rights for authors in relation to the use of their works by platforms, and (ii) whether fairness is perceived as connected with additional aspects, such as the role of online platforms in fostering cultural diversity, the creation of a level playing field for independent digital distribution platforms, etc. We will place special emphasis on the perception and use of algorithms (for instance: recommender systems) by authors and music professionals, seeking to explore how they understand algorithms’ influence and whether they adapt their works to fit the platforms’ expectations. Data collection will draw on an online panel survey involving participants from the digital industry and music associations in Fair MusE’s eight countries of investigation (Portugal, Austria, Belgium, Denmark, Estonia, France, Greece, and Italy). Potential differences between Member States deriving from the size of the music market and their different systems of subsidies to the music sector will meaningfully enrich the analysis.

C. Online music platforms from a business model angle

Our analysis will finally map business models, combining research methods including desk research, expert interviews, and case studies. Our framework for mapping innovative business models will be based to a large extent on the Business Model Matrix Footnote 97 and the Business Model Canvas. Footnote 98 Based on the main types of actors identified previously, this work will produce a two-step business model analysis. First, based on a quick-scan analysis, Footnote 99 we will map all the main business model features of all the main types of stakeholders. It is expected that these main stakeholder categories are authors, distributors, and (playlist) curators. Second, we will conduct an in-depth analysis of at least six platforms with innovative models that are active in the EU. While online platforms have already been largely defined and researched, an in-depth analysis of online music platforms from a business model angle is still missing. We will conduct semi-structured interviews with selected organisations and companies to produce in-depth case studies.

5.1.3 Consumers, Platforms, and Music Diversity

A. In-depth assessment of the influence of algorithms on music consumption

Finally, Phase 1 of our research will include the consumer side of platforms, trying to analyse how these platforms and their algorithms impact consumers and, conversely, the strategies end-users may deploy to access, discover, and remain informed about music thanks to, or despite, platforms. This is also crucial for EU policymakers to effectively promote a fair and sustainable ecosystem. This work will help us make a synthesis of the various issues that have been encountered in research so far, especially as regards the practical effects of algorithms’ design (including recommender systems and playlists) on internet users.

B. Quantitative approach and data analysis

Our team will examine the effective influence of algorithms in the context of music recommender systems by using a quantitative approach and data analysis. We will rely on existing methods in the analysis of recommender systems, Footnote 100 extending Snickars and Mähler’s Footnote 101 analysis of algorithms beyond Spotify. Footnote 102 We will apply a broader and innovative approach to the collection of playlist data by replacing stereotypical fictitious users with +1000 real users who will donate their platform-derived data. Footnote 103 We will compare the +1000 anonymised playlists against each other and against playlists from 80 broadcast radio channels (i.e. ten from each of the eight EU countries within the consortium). This way we will be able to map playlist patterns; characterise diversity and bias in personalised playlists – which represents actual listening – with the curated playlists coming from broadcast radios. Qualitative in-depth interviews on music habits, perceptions of bias, Footnote 104 diversity, and serendipity with approximately 100 users (selected among those who donate their historical playlist data) will add a qualitative dimension to the interpretation of the playlist data. Interviews with broadcast editors responsible for playlists, curation, editorial profile, and rotation policies, and with representatives of online music platforms, will add an interpretative dimension to the analysis of broadcast music programming.

C. Fairness indicators

Finally, based on our previous work, our research team will produce fairness indicators in terms of platform transparency Footnote 105 and bias in recommender systems – as in Htun Footnote 106 and Mehrotra Footnote 107 – regarding algorithmic systems that are currently being used by the online platforms under scrutiny. By characterising the mechanics of the music recommender system algorithms as well the programming policies of many broadcast channels, our research team will highlight effective variables that indicate whether a given platform is fair and gives rise to a sustainable music business, while further suggesting a predictive model that can mitigate the adverse effects of these algorithms from a music diversity perspective.

5.2 Phase 2

In Phase 2 (M25–M36) we envisage the delivery of research outcomes to policymakers and stakeholders (Sections. 5.2.1 , 5.2.2 , and 5.2.3 ) alongside a comprehensive set of policy recommendations embedded in a White Paper on fairness in Europe’s music ecosystems (Section 5.2.4 ).

5.2.1 Music Copyright Infrastructure

In order to be fair, the increasingly platform-dominated music ecosystem needs to address the current lack of adequate data infrastructures through standardisation and sharing of content identifiers and music repertoire information, without which online music exploitations cannot be rewarded in a fair and proportionate way. To this end, we intend to develop a pilot named “Music Copyright Infrastructure”, the main goal of which is to help stakeholders target and solve the problem of information asymmetry across online platforms and right-holders – an asymmetry that is detrimental to all parties, including consumers interested in the diversity of music. We know that online music exploiters have turned data into their main asset (namely: massive, real-time data about their users, music consumption, and hence online music revenues). Considering prior efforts to solve these data asymmetries and their failures, due to participant concerns about the control of data and costs, we will provide a model agreement (and a set of guidelines) to help right-holders and licensees such as online platforms conclude music data-sharing agreements. In our view, these model agreements can help prioritise disclosure over enclosure (or secrecy) and can be directly tested by Fair MusE’s industry partners during the last year of project development.

5.2.2 Music Data Dashboard

The consortium will develop a demo of a Music Data Dashboard of statistical indicators for the European music sector to serve the information needs of policymakers, music professionals, and other stakeholders in this sector. This Dashboard will enable users to get a better understanding of evolutions related to the digitalisation and platformisation of the European music sectors by proposing or identifying indicators and data collection methods. Moreover, the Dashboard will incorporate a link to national statistical institutes, where appropriate. In short, we will (i) review current statistical sources of data on music at the EU and national levels, thus analysing statistical shortcomings in current sources, particularly regarding online music consumption and revenues; (ii) validate the data identified as well as the structure and the objectives of this tool during a “co-creation” policy workshop that involves policymakers; and, eventually; and (iii) deliver a demo for the Dashboard.

5.2.3 Fairness Score

The consortium partners will use the result of the business models analysis and of platform algorithms to set up a tool to assess music services and social media. A “Fairness Score” can become an effective tool to evaluate how online music platforms concretely deal with the criteria and goals EU policymakers intend to foster in the digital media environment. Each criterion, in its definition and assessment, will rely on the work performed in Phase 1 and will be reflected in the White Paper’s recommendations.

The Fairness Score will include the following indicative list of criteria: (i) governance in platform/social media; Footnote 108 (ii) market/non-market values; Footnote 109 (iii) local and national music in content online; Footnote 110 (iv) rights for creators, including access to data regarding their works and the exploitation thereof; Footnote 111 (v) fair and proportionate remuneration; Footnote 112 (vi) business model of the platform/social media; Footnote 113 (vii) gender equality; Footnote 114 (viii) small and medium-size producers vis-à-vis “superstars”; Footnote 115 and (ix) promotion of diversity in the algorithm. Footnote 116

Our Score will either be shaped as an industry-led solution or – on the grounds of data disclosure obligations that arise under EU law (cf. GDPR, DSA, DMA) Footnote 117 – as a soft-law policy instrument or a proper legislative instrument. We assume that this instrument could help EU policymakers influence platform/social media’s practices and conduct at various levels: legal (for instance, in terms of compliance with EU artists’ rights and copyright contract law); economic (for example, as regards fair and transparent remuneration); and social (promotion of cultural and gender diversity); and technical (algorithmic transparency).

5.2.4 Policy Recommendations: White Paper on Fairness in the Music Sector

Our policy recommendations will draw upon the above-mentioned research results, especially the in-depth analysis of new EU law measures aimed at promoting fairness and transparency towards music creators. On the grounds of an interdisciplinary analysis of the consequences of recent EU legislative measures, and of the related national transpositions, our Policy Recommendations will detail tools and actions to facilitate the exercise of creators’ rights through adequate data infrastructures. More precisely, we will include recommendations on the main objectives of Fair MusE: (i) whether and how today’s music industry can significantly improve and evolve in terms of transparency and fairness; (ii) whether and how, from both a legal and technological standpoint, the music sector can develop reliable, standardised, and unequivocal rights ownership information to be able to remunerate individual creators in a fair and proportionate way; and (iii) how legislative or industry-led solutions can reduce or minimise risks created by the enhanced dominance of the largest online music platforms.

6 Conclusion

In this manifesto , we advocate a new, interdisciplinary research approach that can remedy the shortcomings of a purely “silo-like” analysis of EU cultural and industrial policies in the music sector and of their effective impact in today’s platform- and algorithm-dominated economy. The music industry is an interesting case to apply this approach to, as it has gone through radical changes in the past two decades because of the extreme fragmentation of the rights, business interests, and artistic prerogatives that characterise the related creative communities. This has led to significant reforms of the legal and regulatory frameworks governing and shaping European music ecosystems, particularly those embodied in the 2019 Copyright Directive. This directive constitutes a “big bang” in the European history of copyright and artists’ rights, whose real effects are yet to be evaluated in a non-doctrinal and evidence-based way.

Approaching such changes, and in particular the multi-faceted concept of fairness, requires interdisciplinary expertise. This should include policy, legal, economic, and computer science perspectives. In Fair MusE, we analyse the EU as a policymaker in the music industry; we examine the legal framework regarding copyright, contract law, and platform liability; we study music professionals and how value networks have evolved; we assess how algorithms influence music consumption. We involve the music industry, notably via industry partners, members of our Advisory Board and other experts representing the tech and music industries, as well as the community of independent legal practitioners in several European countries. This does not go without challenges: overcoming data secrecy; dealing with opposing interests that govern strategic decisions in the music sector; and ensuring a harmonious collaboration between the diverse disciplines combined in Fair MusE. The last section describes briefly how we will do it, with a quick overview of the tasks and the main expected outcomes.

One point we are especially interested in is the EU’s policy responses. The 2019 Copyright Directive, with its provisions on the copyright liability of social media platforms (Art. 17), the fair and proportionate remuneration of authors and performers (Art. 18), and the codification of a right to transparency and access to data on the earnings generated by creative works (Art. 19), has an exceptional potential to strengthen the bargaining power of individual right-holders and their respective collecting societies in digital markets. The above-mentioned policy changes can become even more effective if we consider the entry into force of other instruments embodied in EU regulations, such as the DSA and the DMA, which are designed to significantly increase the level of responsiveness, internal risk assessment, and accountability of VLOPs and gatekeepers. This new array of EU law provisions targeted at the platform economy can certainly help address some of the existential questions raised by the largest online intermediaries’ ability to control consumers’ access to music repertoires and, at the same time, creators’ content distribution strategies and remuneration opportunities.

We argue that a proper evaluation of these recent developments in EU law should be supported by clear evidence. Such evidence can be built only through interdisciplinary efforts by independent researchers. We know that, to be effective and desirable as a policy instrument, the multi-faceted – and somehow open-ended – notion of “fairness” (used in key EU law provisions, and in many judgments of the ECJ in the copyright law sphere) needs to be dissected and analysed from a legal, policy, economic, and technological perspective, embracing a simultaneously balanced and multi-stakeholder viewpoint. That is the main reason why we promoted the creation of a consortium like Fair MusE, and why we intend to involve several categories of music professionals as well as representatives of industry and civil society in the co-creation of the project’s outcomes. Beyond the music-specific character of our interdisciplinary analysis, we are confident that our research results can also be very useful for other creative industries and media environments – including the news publishing sector – where data-driven exploitations and artificial intelligence have become pervasive and are inevitably changing the processes of content value creation and control and re-shaping ecosystems.

Change history

26 february 2024.

A Correction to this paper has been published: https://doi.org/10.1007/s40319-024-01435-x

Regulation (EU) 2022/2065 of the European Parliament and of the Council of 19 October 2022 on a Single Market For Digital Services and amending Directive 2000/31/EC [2022] OJ L277/1 (“DSA”). See Chapter 3, Section 5.

Regulation (EU) 2022/1925 of the European Parliament and of the Council of 14 September 2022 on contestable and fair markets in the digital sector and amending Directives (EU) 2019/1937 and (EU) 2020/1828 [2022] OJ L265/1 (“DMA”): see Art. 2 and Art. 3.

Promoting Fairness of the Music Ecosystem in a Platform-Dominated and Post-Pandemic Europe (“Fair MusE”), Grant agreement ID: 101095088, https://cordis.europa.eu/project/id/101095088 , accessed on 2 November 2023.

The academic members of the consortium are: Universidade Católica Portuguesa (UCP); Vrije Universiteit Brussel (VUB); Aalborg Universitet (AAU); Université de Lille (ULILLE); Université de Liège (ULIEGE); Hellenic Foundation for European and Foreign Policy (ELIAMEP); Tartu Ülikool (UTARTU); Central European University Gmbh (CEU).

https://www.siae.it .

https://www.verifi.media .

The European Commission’s recent legislative initiatives in the areas of standard essential patents, artificial intelligence, platform-to-business trading practices, as well as competition law all rely on fairness as one of their objectives, namely: Proposal for a Regulation of the European Parliament and of the Council on standard essential patents and amending Regulation (EU) 2017/1001 [2023] COM(2023) 232 final; Proposal for a Regulation of the European Parliament and of the Council laying down harmonised rules on artificial intelligence and amending certain Union legislative acts [2021] COM/2021/206 final (“Draft Artificial Intelligence Act”); Regulation (EU) 2019/1150 of the European Parliament and of the Council of 20 June 2019 on promoting fairness and transparency for business users of online intermediation services [2019] OJ L186/57 (“Platform-to-Business Regulation”). Regulation (EU) 2022/1925 ( supra note 2).

Statistics evidenced a dramatic fall of the music business between 1999 and 2014, when global revenues from physical and digital music sales declined by 42%, from $25.2 to 14.6 billion. See IFPI, “Global Music Report 2018: Annual State of the Industry” https://www.ifpi.org/ifpi-global-music-report-2018/ , accessed 2 November 2023.

“Value gap” is an expression used for the first time by representatives of the music industry in Brussels to describe the impoverishment of their sector as a consequence of widely uncompensated uses of copyright works across online platforms and a sharp difference between the licensing fees paid by social media and the fees paid by music streaming services: see , for instance, Smith, Desbrosses and Moore ( 2016 ).

Cunningham and Craig ( 2019 ), pp. 11–14.

Directive (EU) 2019/790 of the European Parliament and of the Council of 17 April 2019 on copyright and related rights in the Digital Single Market and amending Directives 96/9/EC and 2001/29/EC [2019] OJ L130/92 (“2019 Copyright Directive”).

2019 Copyright Directive, Art. 17.

2019 Copyright Directive, Art. 18.

2019 Copyright Directive, Art. 19.

Wikström ( 2020 ), p. 367.

Laing ( 1999 ), p. 31; Sarikakis ( 2007 ); Littoz-Monnet ( 2007 ); Iosifidis ( 2011 ); Donders et al. ( 2014 ).

See European Commission, “Music Moves Europe”: https://culture.ec.europa.eu/cultural-and-creative-sectors/music/music-moves-europe , accessed 2 November 2023.

The complex infrastructure of the DSA is designed not to interfere, but rather to be complementary with the copyright-specific mechanism of Art. 17: see on this topic, Quintais and Schwemer ( 2022 ), p. 191; Rosati ( 2021 ).

Directive 2000/31/EC of the European Parliament and of the Council of 8 June 2000 on certain legal aspects of information society services, in particular electronic commerce, in the Internal Market [2000] OJ L178/1 (“e-Commerce Directive”).

A non-exhaustive list of these initiatives includes the following ones: Sophie Stalla-Bourdillon et al (40 academics), Open Letter to the European Commission – On the Importance of Preserving the Consistency and Integrity of the EU Acquis Relating to Content Monitoring within the Information Society, available at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2850483 , accessed on 2 November 2023; European Copyright Society, “General Opinion on the EU Copyright Reform Package”, 2017, available at https://europeancopyrightsocietydotorg.files.wordpress.com/2015/12/ecs-opinion-on-eu-copyright-reform-def.pdf , accessed on 2 November 2023; Max Planck Institute for Innovation and Competition (2017), Position Statement on the Proposed Modernization of European Copyright Rules: Art. 13, available at: https://www.ip.mpg.de/fileadmin/ipmpg/content/stellungnahmen/MPI_Position_Statement_PART_G_incl_Annex-2017_03_01.pdf , accessed on 2 November 2023. See also Cory Doctorow, “Four million Europeans’ signatures opposing Article 13 have been delivered to the European Parliament” (EFF, 10 December 2018) https://www.eff.org/deeplinks/2018/12/four-million-europeans-signatures-opposing-article-13-have-been-delivered-european , accessed on 2 November 2023. Among the academic contributions following the adoption of the directive, see Dusollier ( 2020 ), p. 979, who describes Art. 17 as a “monster provision” considering its size and “hazardousness”. At an earlier stage, very critical scholars included Frosio ( 2017 ), p. 565; and Senftleben et al. ( 2018 ).

Rosati ( 2022 ), p. 397.

Although this initiative was consistent with Poland’s dissenting vote at the time the EU Council adopted Directive 2019/790, this case suddenly transformed the Polish government, a notorious antagonist (at least until very recently) of EU institutions vis-à-vis the affirmation of human rights and the rule of law, into a noble and tireless paladin of freedom of expression: see C-401/19 Poland v. Parliament and Council , ECLI:EU:C:2022:297. It is worth recalling that the Polish rule-of-law crisis culminated in infringement proceedings launched by the European Commission against Poland, alleging a failure to fulfil its obligations under Art. 19(1)(2) of the Treaty of the European Union (TEU) and Art. 47 of the Charter of the Fundamental Rights of the European Union. In the subsequent appeal, the ECJ ruled that Poland indeed infringed the principle of judicial independence under Art. 19(1)(2) TEU when lowering the retirement age of Supreme Court judges: see case C-619/18 European Commission v. Republic of Poland , ECLI:EU:C:2019:531.

A good example of scholars’ focus on the importance of safeguarding users’ freedom of expression and information in the online environment when implementing Art. 17 of the 2019 Copyright Directive is provided by Quintais et al. ( 2019 ), pp. 277–282. In a similar way, Geiger and Jütte claim that Art. 17 fails to properly address the need to strike a fair balance between competing interests, emphasising the negative effect of filtering mechanisms on users’ fundamental rights: see Geiger and Jütte ( 2021 ), pp. 532–534. Other contributions emphasise how Art. 17 can negatively impact on the platforms’ freedom to conduct business: see , for instance, Reda et al. ( 2020 ), at pp. 42–49, claiming that the provisions of Art. 17 are not capable of achieving a fair balance between the fundamental right to conduct a business and other rights, as they place a significant economic burden on online content-sharing service providers. See also Geiger and Jütte, mentioned above, p. 542, maintaining that Art. 17 imposes immense obligations on social media platforms, restricting their freedom to conduct a business.

Among the most recent judgments, see , for instance, ECtHR Fredrik Neij and Peter Sunde Kolmisoppi (The Pirate Bay) v. Sweden , 40397/12, where the Court stressed that intellectual property – more specifically the “rights of the copyright-holders” – is a form of “property” that benefits from the protection afforded by Art. 1 of Protocol No. 1 to the ECHR against unauthorised dissemination of protected works through file-sharing technologies. At an earlier stage, ECtHR Case Ashby Donald et autres v. France , 36769/08 founded the protection of the copyright of fashion houses in their own creations (against unauthorised photographers invoking their right to freedom of expression) again on the grounds of the constitutional protection of “property” under Art. 1 of Protocol No. 1 of the ECHR. For a detailed review of the ECtHR case law on intellectual property rights, see Geiger and Izyumenko ( 2018 ), p. 9.

In C-401/19 Poland v. Parliament and Council , the ECJ provides an analysis of the principle of proportionality under paras. 63–69 and explicitly states, in para. 82, that “in the context of the review of proportionality referred to in Article 52(1) of the Charter, it must be noted, first of all, that the limitation on the exercise of the right to freedom of expression and information of users of online content-sharing services, referred to in paragraph 69 above, meets the need to protect the rights and freedoms of others within the meaning of Article 52(1) of the Charter, that is, in this case, the need to protect intellectual property guaranteed in Article 17(2) of the Charter.”

See C-401/19 Poland v. Parliament and Council , paras. 92–99.

See Strowel ( 2020 ), pp. 40–46, who emphasises how the constant, explicit reference to intellectual property as a fundamental right in the case law of the ECJ has played a central role in strengthening the protection and enforcement of copyright, especially in digital settings. As argued by this author, this explicit recognition under EU law provides an even stronger foundation for the qualification of authors’ rights as human rights. This is consistent with Art. 27(2) of the 1948 Universal Declaration of Human Rights at the international level, which protects the moral and material interests of authors resulting from their scientific, literary, or artistic productions. It is worth recalling that while the concept of authors’ rights as moral rights is eminently European, it is gaining traction because of technological challenges even in systems – like the United States – that have historically neglected this concept: see , for instance, Sundara Rajan ( 2019 ), pp. 257–258.

As stressed by Strowel ( 2020 ), pp. 40–52, the recent case law of the ECJ reveals a careful approach in the examination of copyright disputes in the digital environment. The author stresses how, in several cases, the principle of fair balance made copyright claims prevail over defences based on freedom of expression and other fundamental rights (such as the right to privacy) because of the necessity to guarantee a high level of protection to intellectual property rights, as embodied in the EU legislation and as requested under Art. 17(2) of the EU Charter of Fundamental Rights. See , for instance: C-275/06 Promusicae v. Telefonica , ECLI:EU:C:2008:54; C-160/15 GS Media v. Sanoma et al. , ECLI:EU:C:2016:644; Case C-161/17 Land Nordrhein-Westfalen v. Dirk Renckoff , ECLI: EU:C:2018:634; C-476/17 Pelham GmbH and Others v. Ralf Hütter and Florian Schneider-Esleben , ECLI:EU:C: 2019:624.

For a more positive view on Art. 17’s impact on fundamental rights, see , for instance, Cabay ( 2020 ).

Mazziotti ( 2021 ).

The fact that prior attempts to improve rights information through standard tools such as the Global Repertoire Database (GRD) have largely failed can help solve a data-sharing dilemma that has only grown worse with the exponential increase in the availability of content on access-based platforms. On the failure of the GRD see , for instance, Milosic ( 2015 ).

Directive 2014/26/EU of the European Parliament and of the Council of 26 February 2014 on collective management of copyright and related rights and multi-territorial licensing of rights in musical works for online use in the internal market [2014] OJ L84/72 (“CRM Directive”).

Draft Artificial Intelligence Act ( supra note 7).

Proposal for a Regulation of the European Parliament and of the Council on harmonised rules on fair access to and use of data [2022] COM(2022) 68 final (“Draft Data Act”).

Rochet and Tirole ( 2002 ), p. 549; Poell et al. ( 2019 ), p. 1; Evans et al. ( 2005 ), p. 189.

Rochet and Tirole ( 2006 ), p. 645.

Luck ( 2016 ), p. 46.

Poell et al. ( 2019 ); Vlassis et al. ( 2020 ).

Van Audenhove et al. ( 2016 ).

Croll ( 2015 ).

Kastrenakes ( 2019 ).

Iqbal ( 2023 ).

Ferraro et al. ( 2021 ).

Vlassis et al. ( 2020 ).

Mazziotti ( 2020 ), p. 1027.

Flew and Gillett ( 2021 ), p. 231.

Castells et al. ( 2015 ).

Zarsky ( 2016 ), p. 118.

Bozdag and Van Den Hoven ( 2015 ), p. 249.

Helberger ( 2012 ), p. 65.

Bozdag ( 2013 ), p. 209.

Noble ( 2018 ).

Nechushtai and Lewis ( 2019 ), p. 298.

Chen et al. ( 2020 ).

Masnick and Ho ( 2014 ).

Gourville and Soman ( 2005 ), p. 382.

Kunaver and Požrl ( 2017 ), p. 154.

Haim et al. ( 2018 ), p. 330.

Snickars ( 2017 ), p. 184; Snickars and Mähler ( 2018 ).

Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC [2016] OJ L119/1 (“GDPR”).

Human-Num is a French infrastructure that aims at supporting research communities by providing services, assessments, and tools for digital research data. See https://www.huma-num.fr/ , accessed on 2 November 2023.

See https://github.com/dataiku , accessed on 2 November 2023.

Melchiorre et al. ( 2021 ) p. 1.

See various legislative initiatives of the European Commission, cited above ( supra note 7).

See the Treaty on the Functioning of the European Union (TFEU), Art. 167, para. 4.

Johansson et al. ( 2018 ), p. 165.

Mazziotti ( 2021 ), pp. 214–215.

Scott et al. ( 1990 ), pp. 474–494.

D’Agostino ( 1995 ), pp. 396–405.

König and Gorman ( 2017 ).

Friedman ( 2013 ).

De Rond and Miller ( 2005 ), p. 321.

Lach ( 2014 ), pp. 88–93.

Rogers et al. ( 2005 ).

Villeneuve et al. ( 2020 ), p. 197.

Sanz-Menéndez et al. ( 2001 ), pp. 47–58.

Relevant instruments and reports include: Directive 2000/31/EC of the European Parliament and of the Council of 8 June 2000 on certain legal aspects of information society services, in particular electronic commerce, in the Internal Market (2000) OJ L178/1 (“e-Commerce Directive”); Directive 2001/29/EC of the European Parliament and of the Council of 22 May 2001 on the harmonisation of certain aspects of copyright and related rights in the information society (2001) OJ L167/10; Regulatory framework for electronic communications and services (2003); Commission, “A Digital Agenda for Europe” (Communication) COM (2010) 245 final; Commission, “A Digital Single Market Strategy for Europe” (Communication) COM (2015) 0192 final; Commission, “The AB Music Working Group Report” (2016) Publications Office of the European Union https://op.europa.eu/en/publication-detail/-/publication/f5479d95-2fca-11e7-9412-01aa75ed71a1 , accessed on 2 November 2023; Commission, “New European Agenda for Culture” (Communication) COM (2018) 267 final; Commission, “Proposal for a Regulation establishing the New Creative Europe programme” COM (2018) 366 final; Council Conclusions on the Work Plan for Culture 2019-2022 [2018] OJ C460/12; Commission, “Music Moves Europe – First Dialogue Meeting-Report” (2019) https://culture.ec.europa.eu/sites/default/files/library/mme-conference-report-web.pdf , accessed on 2 November 2023; 2019 Copyright Directive; Proposal for a Regulation of the European Parliament and of the Council on contestable and fair markets in the digital sector (Digital Markets Act) COM (2020) 842 final; Proposal for a Regulation of the European Parliament and of the Council on a Single Market For Digital Services (Digital Services Act) and amending Directive 2000/31/EC COM (2020) 825 final; Commission, ‘Report from the Conference ‘Diversity and Competitiveness of the European Music Sector’ with EU Member States Experts” (2021) https://culture.ec.europa.eu/document/report-conference-diversity-and-competitiveness-european-music-sector-eu-member-states-experts , accessed on 2 November 2023.

Commission, “Music Moves Europe – First Dialogue Meeting-Report” (2019) https://culture.ec.europa.eu/sites/default/files/library/mme-conference-report-web.pdf , accessed on 2 November 2023.

See various legislative initiatives of the European Commission, cited above ( supra note7).

Directive 2001/29/EC of the European Parliament and of the Council of 22 May 2001 on the harmonisation of certain aspects of copyright and related rights in the information society [2001] OJ L167/10 (“Information Society Directive”).

Arts. 33–43 DSA.

On this front, our analysis will be comparative in nature. Namely, it will compare the copyright treatment of user-generated content platforms under EU and US law, in particular the case law based upon the US Digital Millennium Copyright Act (DMCA) 1998, which amended the US Copyright Act (17 US Code), Section 512(c).

For the full list of the Advisory Board’s members, see the Fair Muse’s website at https://fairmuse.eu/team/ , accessed on 2 November 2023.

Cunningham and Craig ( 2019 ), p. 15, where the authors emphasise that social media entertainment has, from the beginning, a global dimension because its content is not primarily based on intellectual property’s territorial control (as it is, instead, in the film and TV broadcasting sectors); Mazziotti ( 2021 ).

CRM Directive ( supra note 32).

Ranaivoson et al. ( 2013 ), p. 665.

The project also aims to consider the recent actions of the French, German, and Italian competition authorities, which have been particularly active in enforcing competition rules against large online platforms. See , for instance, as regards the French Competition Authority: Decision 21-D-11 of June 07, 2021, against Google regarding practices implemented in the online advertising sector; Decision 22-D-12 of June 16, 2022, against Meta regarding practices implemented in the online advertising sector. As regards the German Competition Authority, see Decision B6-22/16 of 6 February 2019 against Facebook for data handling practices; Decision V-43/20 of 21 December 2022 against Google for data handling practices in the case of Google News Showcases. In Italy, see the proceedings launched in April 2023 by the Italian Competition Authority against Meta for abuse of economic dependence towards SIAE, available at https://www.agcm.it/dotcmsdoc/allegati-news/A559%20avvio%20e%20caut.pdf , accessed on 2 November 2023.

See , for instance, Wu ( 2018 ), p. 132.

De Voldere et al. ( 2017 ).

Kostovska et al. ( 2021 ), pp. 6–26.

Negus ( 2019 ), p. 367.

DIGITALEUROPE is an organisation that represents the digital technology sector in Europe. See https://www.digitaleurope.org/ , accessed on 2 November 2023.

DOT Europe is an association of the main internet companies active in Europe, including leading social media and streaming platforms. See https://doteurope.eu/ , accessed on 2 November 2023.

European live music association is a non-profit organisation that supports the European live music industries. See https://www.elmnet.org/ , accessed on 2 November 2023.

European Music Council is a non-profit organisation whose mission is to develop and promote music of all genres and types. See https://www.emc-imc.org/ , accessed on 2 November 2023.

European Composer and Songwriter Alliance (ECSA) focuses on protecting and advancing the rights of composers and songwriters. See https://composeralliance.org/ , accessed on 2 November 2023.

IMPALA is the European organisation for independent music companies and national associations. See https://www.impalamusic.org/ , accessed on 2 November 2023.

Ballon ( 2007 ), p. 6.

Osterwalder and Pigneur ( 2010 ).

Loecherbach and Trilling ( 2020 ), p. 53.

Snickars and Mähler ( 2018 ).

Ferraro et al. ( 2019 ).

Puschmann ( 2019 ), p. 824.

Melchiorre et al. ( 2021 ).

Htun et al. ( 2021 ).

Mehrotra et al. ( 2018 ).

Based on the research conducted by the politics research hub of Fair MusE, as elaborated in Section 3.1 .

See the discussion in Section 3.1 above.

See an overview of the relevant issues in Section 4.2 above.

From both legal and economic perspectives, as elaborated in Sections 5.1.1 B, E, F and 5.1.2 A.

See Section 5.1.2 above.

As laid down in the Fair MusE’s Gender Action Plan.

See the discussion in Section 4.2 concerning the impact of algorithms on the discoverability of niche or marginal repertoires.

See Section 5.1.3 above.

Art. 20(1) GDPR, Art. 40 DSA, Art. 6(9) DMA. In particular, the European Commission is preparing a Delegated Regulation on data access obligations of very large online platforms (VLOPs) and very large search engines (VLSEs) on the grounds of Art. 40 of the DSA. To this end, the Commission launched a call for evidence, to which Fair MusE’s researchers submitted a publicly available response: https://ec.europa.eu/info/law/better-regulation/have-your-say/initiatives/13817-Delegated-Regulation-on-data-access-provided-for-in-the-Digital-Services-Act/F3423886_en , accessed on 2 November 2023.

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• Published: 17 October 2023

The impact of founder personalities on startup success

• Paul X. McCarthy 1 , 2 ,
• Xian Gong 3 ,
• Fabian Braesemann 4 , 5 ,
• Fabian Stephany 4 , 5 ,
• Marian-Andrei Rizoiu 3 &
• Margaret L. Kern 6  

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Startup companies solve many of today’s most challenging problems, such as the decarbonisation of the economy or the development of novel life-saving vaccines. Startups are a vital source of innovation, yet the most innovative are also the least likely to survive. The probability of success of startups has been shown to relate to several firm-level factors such as industry, location and the economy of the day. Still, attention has increasingly considered internal factors relating to the firm’s founding team, including their previous experiences and failures, their centrality in a global network of other founders and investors, as well as the team’s size. The effects of founders’ personalities on the success of new ventures are, however, mainly unknown. Here, we show that founder personality traits are a significant feature of a firm’s ultimate success. We draw upon detailed data about the success of a large-scale global sample of startups (n = 21,187). We find that the Big Five personality traits of startup founders across 30 dimensions significantly differ from that of the population at large. Key personality facets that distinguish successful entrepreneurs include a preference for variety, novelty and starting new things (openness to adventure), like being the centre of attention (lower levels of modesty) and being exuberant (higher activity levels). We do not find one ’Founder-type’ personality; instead, six different personality types appear. Our results also demonstrate the benefits of larger, personality-diverse teams in startups, which show an increased likelihood of success. The findings emphasise the role of the diversity of personality types as a novel dimension of team diversity that influences performance and success.

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Introduction.

The success of startups is vital to economic growth and renewal, with a small number of young, high-growth firms creating a disproportionately large share of all new jobs 1 , 2 . Startups create jobs and drive economic growth, and they are also an essential vehicle for solving some of society’s most pressing challenges.

As a poignant example, six centuries ago, the German city of Mainz was abuzz as the birthplace of the world’s first moveable-type press created by Johannes Gutenberg. However, in the early part of this century, it faced several economic challenges, including rising unemployment and a significant and growing municipal debt. Then in 2008, two Turkish immigrants formed the company BioNTech in Mainz with another university research colleague. Together they pioneered new mRNA-based technologies. In 2020, BioNTech partnered with US pharmaceutical giant Pfizer to create one of only a handful of vaccines worldwide for Covid-19, saving an estimated six million lives 3 . The economic benefit to Europe and, in particular, the German city where the vaccine was developed has been significant, with windfall tax receipts to the government clearing Mainz’s €1.3bn debt and enabling tax rates to be reduced, attracting other businesses to the region as well as inspiring a whole new generation of startups 4 .

While stories such as the success of BioNTech are often retold and remembered, their success is the exception rather than the rule. The overwhelming majority of startups ultimately fail. One study of 775 startups in Canada that successfully attracted external investment found only 35% were still operating seven years later 5 .

But what determines the success of these ‘lucky few’? When assessing the success factors of startups, especially in the early-stage unproven phase, venture capitalists and other investors offer valuable insights. Three different schools of thought characterise their perspectives: first, supply-side or product investors : those who prioritise investing in firms they consider to have novel and superior products and services, investing in companies with intellectual property such as patents and trademarks. Secondly, demand-side or market-based investors : those who prioritise investing in areas of highest market interest, such as in hot areas of technology like quantum computing or recurrent or emerging large-scale social and economic challenges such as the decarbonisation of the economy. Thirdly, talent investors : those who prioritise the foundation team above the startup’s initial products or what industry or problem it is looking to address.

Investors who adopt the third perspective and prioritise talent often recognise that a good team can overcome many challenges in the lead-up to product-market fit. And while the initial products of a startup may or may not work a successful and well-functioning team has the potential to pivot to new markets and new products, even if the initial ones prove untenable. Not surprisingly, an industry ‘autopsy’ into 101 tech startup failures found 23% were due to not having the right team—the number three cause of failure ahead of running out of cash or not having a product that meets the market need 6 .

Accordingly, early entrepreneurship research was focused on the personality of founders, but the focus shifted away in the mid-1980s onwards towards more environmental factors such as venture capital financing 7 , 8 , 9 , networks 10 , location 11 and due to a range of issues and challenges identified with the early entrepreneurship personality research 12 , 13 . At the turn of the 21st century, some scholars began exploring ways to combine context and personality and reconcile entrepreneurs’ individual traits with features of their environment. In her influential work ’The Sociology of Entrepreneurship’, Patricia H. Thornton 14 discusses two perspectives on entrepreneurship: the supply-side perspective (personality theory) and the demand-side perspective (environmental approach). The supply-side perspective focuses on the individual traits of entrepreneurs. In contrast, the demand-side perspective focuses on the context in which entrepreneurship occurs, with factors such as finance, industry and geography each playing their part. In the past two decades, there has been a revival of interest and research that explores how entrepreneurs’ personality relates to the success of their ventures. This new and growing body of research includes several reviews and meta-studies, which show that personality traits play an important role in both career success and entrepreneurship 15 , 16 , 17 , 18 , 19 , that there is heterogeneity in definitions and samples used in research on entrepreneurship 16 , 18 , and that founder personality plays an important role in overall startup outcomes 17 , 19 .

Motivated by the pivotal role of the personality of founders on startup success outlined in these recent contributions, we investigate two main research questions:

Which personality features characterise founders?

Do their personalities, particularly the diversity of personality types in founder teams, play a role in startup success?

We aim to understand whether certain founder personalities and their combinations relate to startup success, defined as whether their company has been acquired, acquired another company or listed on a public stock exchange. For the quantitative analysis, we draw on a previously published methodology 20 , which matches people to their ‘ideal’ jobs based on social media-inferred personality traits.

We find that personality traits matter for startup success. In addition to firm-level factors of location, industry and company age, we show that founders’ specific Big Five personality traits, such as adventurousness and openness, are significantly more widespread among successful startups. As we find that companies with multi-founder teams are more likely to succeed, we cluster founders in six different and distinct personality groups to underline the relevance of the complementarity in personality traits among founder teams. Startups with diverse and specific combinations of founder types (e. g., an adventurous ‘Leader’, a conscientious ‘Accomplisher’, and an extroverted ‘Developer’) have significantly higher odds of success.

We organise the rest of this paper as follows. In the Section " Results ", we introduce the data used and the methods applied to relate founders’ psychological traits with their startups’ success. We introduce the natural language processing method to derive individual and team personality characteristics and the clustering technique to identify personality groups. Then, we present the result for multi-variate regression analysis that allows us to relate firm success with external and personality features. Subsequently, the Section " Discussion " mentions limitations and opportunities for future research in this domain. In the Section " Methods ", we describe the data, the variables in use, and the clustering in greater detail. Robustness checks and additional analyses can be found in the Supplementary Information.

Our analysis relies on two datasets. We infer individual personality facets via a previously published methodology 20 from Twitter user profiles. Here, we restrict our analysis to founders with a Crunchbase profile. Crunchbase is the world’s largest directory on startups. It provides information about more than one million companies, primarily focused on funding and investors. A company’s public Crunchbase profile can be considered a digital business card of an early-stage venture. As such, the founding teams tend to provide information about themselves, including their educational background or a link to their Twitter account.

We infer the personality profiles of the founding teams of early-stage ventures from their publicly available Twitter profiles, using the methodology described by Kern et al. 20 . Then, we correlate this information to data from Crunchbase to determine whether particular combinations of personality traits correspond to the success of early-stage ventures. The final dataset used in the success prediction model contains n = 21,187 startup companies (for more details on the data see the Methods section and SI section  A.5 ).

Revisions of Crunchbase as a data source for investigations on a firm and industry level confirm the platform to be a useful and valuable source of data for startups research, as comparisons with other sources at micro-level, e.g., VentureXpert or PwC, also suggest that the platform’s coverage is very comprehensive, especially for start-ups located in the United States 21 . Moreover, aggregate statistics on funding rounds by country and year are quite similar to those produced with other established sources, going to validate the use of Crunchbase as a reliable source in terms of coverage of funded ventures. For instance, Crunchbase covers about the same number of investment rounds in the analogous sectors as collected by the National Venture Capital Association 22 . However, we acknowledge that the data source might suffer from registration latency (a certain delay between the foundation of the company and its actual registration on Crunchbase) and success bias in company status (the likeliness that failed companies decide to delete their profile from the database).

The definition of startup success

The success of startups is uncertain, dependent on many factors and can be measured in various ways. Due to the likelihood of failure in startups, some large-scale studies have looked at which features predict startup survival rates 23 , and others focus on fundraising from external investors at various stages 24 . Success for startups can be measured in multiple ways, such as the amount of external investment attracted, the number of new products shipped or the annual growth in revenue. But sometimes external investments are misguided, revenue growth can be short-lived, and new products may fail to find traction.

Success in a startup is typically staged and can appear in different forms and times. For example, a startup may be seen to be successful when it finds a clear solution to a widely recognised problem, such as developing a successful vaccine. On the other hand, it could be achieving some measure of commercial success, such as rapidly accelerating sales or becoming profitable or at least cash positive. Or it could be reaching an exit for foundation investors via a trade sale, acquisition or listing of its shares for sale on a public stock exchange via an Initial Public Offering (IPO).

For our study, we focused on the startup’s extrinsic success rather than the founders’ intrinsic success per se, as its more visible, objective and measurable. A frequently considered measure of success is the attraction of external investment by venture capitalists 25 . However, this is not in and of itself a good measure of clear, incontrovertible success, particularly for early-stage ventures. This is because it reflects investors’ expectations of a startup’s success potential rather than actual business success. Similarly, we considered other measures like revenue growth 26 , liquidity events 27 , 28 , 29 , profitability 30 and social impact 31 , all of which have benefits as they capture incremental success, but each also comes with operational measurement challenges.

Therefore, we apply the success definition initially introduced by Bonaventura et al. 32 , namely that a startup is acquired, acquires another company or has an initial public offering (IPO). We consider any of these major capital liquidation events as a clear threshold signal that the company has matured from an early-stage venture to becoming or is on its way to becoming a mature company with clear and often significant business growth prospects. Together these three major liquidity events capture the primary forms of exit for external investors (an acquisition or trade sale and an IPO). For companies with a longer autonomous growth runway, acquiring another company marks a similar milestone of scale, maturity and capability.

Using multifactor analysis and a binary classification prediction model of startup success, we looked at many variables together and their relative influence on the probability of the success of startups. We looked at seven categories of factors through three lenses of firm-level factors: (1) location, (2) industry, (3) age of the startup; founder-level factors: (4) number of founders, (5) gender of founders, (6) personality characteristics of founders and; lastly team-level factors: (7) founder-team personality combinations. The model performance and relative impacts on the probability of startup success of each of these categories of founders are illustrated in more detail in section  A.6 of the Supplementary Information (in particular Extended Data Fig.  19 and Extended Data Fig.  20 ). In total, we considered over three hundred variables (n = 323) and their relative significant associations with success.

The personality of founders

Besides product-market, industry, and firm-level factors (see SI section  A.1 ), research suggests that the personalities of founders play a crucial role in startup success 19 . Therefore, we examine the personality characteristics of individual startup founders and teams of founders in relationship to their firm’s success by applying the success definition used by Bonaventura et al. 32 .

Employing established methods 33 , 34 , 35 , we inferred the personality traits across 30 dimensions (Big Five facets) of a large global sample of startup founders. The startup founders cohort was created from a subset of founders from the global startup industry directory Crunchbase, who are also active on the social media platform Twitter.

To measure the personality of the founders, we used the Big Five, a popular model of personality which includes five core traits: Openness to Experience, Conscientiousness, Extraversion, Agreeableness, and Emotional stability. Each of these traits can be further broken down into thirty distinct facets. Studies have found that the Big Five predict meaningful life outcomes, such as physical and mental health, longevity, social relationships, health-related behaviours, antisocial behaviour, and social contribution, at levels on par with intelligence and socioeconomic status 36 Using machine learning to infer personality traits by analysing the use of language and activity on social media has been shown to be more accurate than predictions of coworkers, friends and family and similar in accuracy to the judgement of spouses 37 . Further, as other research has shown, we assume that personality traits remain stable in adulthood even through significant life events 38 , 39 , 40 . Personality traits have been shown to emerge continuously from those already evident in adolescence 41 and are not significantly influenced by external life events such as becoming divorced or unemployed 42 . This suggests that the direction of any measurable effect goes from founder personalities to startup success and not vice versa.

As a first investigation to what extent personality traits might relate to entrepreneurship, we use the personality characteristics of individuals to predict whether they were an entrepreneur or an employee. We trained and tested a machine-learning random forest classifier to distinguish and classify entrepreneurs from employees and vice-versa using inferred personality vectors alone. As a result, we found we could correctly predict entrepreneurs with 77% accuracy and employees with 88% accuracy (Fig.  1 A). Thus, based on personality information alone, we correctly predict all unseen new samples with 82.5% accuracy (See SI section  A.2 for more details on this analysis, the classification modelling and prediction accuracy).

We explored in greater detail which personality features are most prominent among entrepreneurs. We found that the subdomain or facet of Adventurousness within the Big Five Domain of Openness was significant and had the largest effect size. The facet of Modesty within the Big Five Domain of Agreeableness and Activity Level within the Big Five Domain of Extraversion was the subsequent most considerable effect (Fig.  1 B). Adventurousness in the Big Five framework is defined as the preference for variety, novelty and starting new things—which are consistent with the role of a startup founder whose role, especially in the early life of the company, is to explore things that do not scale easily 43 and is about developing and testing new products, services and business models with the market.

Once we derived and tested the Big Five personality features for each entrepreneur in our data set, we examined whether there is evidence indicating that startup founders naturally cluster according to their personality features using a Hopkins test (see Extended Data Figure  6 ). We discovered clear clustering tendencies in the data compared with other renowned reference data sets known to have clusters. Then, once we established the founder data clusters, we used agglomerative hierarchical clustering. This ‘bottom-up’ clustering technique initially treats each observation as an individual cluster. Then it merges them to create a hierarchy of possible cluster schemes with differing numbers of groups (See Extended Data Fig.  7 ). And lastly, we identified the optimum number of clusters based on the outcome of four different clustering performance measurements: Davies-Bouldin Index, Silhouette coefficients, Calinski-Harabas Index and Dunn Index (see Extended Data Figure  8 ). We find that the optimum number of clusters of startup founders based on their personality features is six (labelled #0 through to #5), as shown in Fig.  1 C.

To better understand the context of different founder types, we positioned each of the six types of founders within an occupation-personality matrix established from previous research 44 . This research showed that ‘each job has its own personality’ using a substantial sample of employees across various jobs. Utilising the methodology employed in this study, we assigned labels to the cluster names #0 to #5, which correspond to the identified occupation tribes that best describe the personality facets represented by the clusters (see Extended Data Fig.  9 for an overview of these tribes, as identified by McCarthy et al. 44 ).

Utilising this approach, we identify three ’purebred’ clusters: #0, #2 and #5, whose members are dominated by a single tribe (larger than 60% of all individuals in each cluster are characterised by one tribe). Thus, these clusters represent and share personality attributes of these previously identified occupation-personality tribes 44 , which have the following known distinctive personality attributes (see also Table  1 ):

Accomplishers (#0) —Organised & outgoing. confident, down-to-earth, content, accommodating, mild-tempered & self-assured.

Leaders (#2) —Adventurous, persistent, dispassionate, assertive, self-controlled, calm under pressure, philosophical, excitement-seeking & confident.

Fighters (#5) —Spontaneous and impulsive, tough, sceptical, and uncompromising.

We labelled these clusters with the tribe names, acknowledging that labels are somewhat arbitrary, based on our best interpretation of the data (See SI section  A.3 for more details).

For the remaining three clusters #1, #3 and #4, we can see they are ‘hybrids’, meaning that the founders within them come from a mix of different tribes, with no one tribe representing more than 50% of the members of that cluster. However, the tribes with the largest share were noted as #1 Experts/Engineers, #3 Fighters, and #4 Operators.

To label these three hybrid clusters, we examined the closest occupations to the median personality features of each cluster. We selected a name that reflected the common themes of these occupations, namely:

Experts/Engineers (#1) as the closest roles included Materials Engineers and Chemical Engineers. This is consistent with this cluster’s personality footprint, which is highest in openness in the facets of imagination and intellect.

Developers (#3) as the closest roles include Application Developers and related technology roles such as Business Systems Analysts and Product Managers.

Operators (#4) as the closest roles include service, maintenance and operations functions, including Bicycle Mechanic, Mechanic and Service Manager. This is also consistent with one of the key personality traits of high conscientiousness in the facet of orderliness and high agreeableness in the facet of humility for founders in this cluster.

Founder-Level Factors of Startup Success. ( A ), Successful entrepreneurs differ from successful employees. They can be accurately distinguished using a classifier with personality information alone. ( B ), Successful entrepreneurs have different Big Five facet distributions, especially on adventurousness, modesty and activity level. ( C ), Founders come in six different types: Fighters, Operators, Accomplishers, Leaders, Engineers and Developers (FOALED) ( D ), Each founder Personality-Type has its distinct facet.

Together, these six different types of startup founders (Fig.  1 C) represent a framework we call the FOALED model of founder types—an acronym of Fighters, Operators, Accomplishers, Leaders, Engineers and D evelopers.

Each founder’s personality type has its distinct facet footprint (for more details, see Extended Data Figure  10 in SI section  A.3 ). Also, we observe a central core of correlated features that are high for all types of entrepreneurs, including intellect, adventurousness and activity level (Fig.  1 D).To test the robustness of the clustering of the personality facets, we compare the mean scores of the individual facets per cluster with a 20-fold resampling of the data and find that the clusters are, overall, largely robust against resampling (see Extended Data Figure  11 in SI section  A.3 for more details).

We also find that the clusters accord with the distribution of founders’ roles in their startups. For example, Accomplishers are often Chief Executive Officers, Chief Financial Officers, or Chief Operating Officers, while Fighters tend to be Chief Technical Officers, Chief Product Officers, or Chief Commercial Officers (see Extended Data Fig.  12 in SI section  A.4 for more details).

The ensemble theory of success

While founders’ individual personality traits, such as Adventurousness or Openness, show to be related to their firms’ success, we also hypothesise that the combination, or ensemble, of personality characteristics of a founding team impacts the chances of success. The logic behind this reasoning is complementarity, which is proposed by contemporary research on the functional roles of founder teams. Examples of these clear functional roles have evolved in established industries such as film and television, construction, and advertising 45 . When we subsequently explored the combinations of personality types among founders and their relationship to the probability of startup success, adjusted for a range of other factors in a multi-factorial analysis, we found significantly increased chances of success for mixed foundation teams:

Initially, we find that firms with multiple founders are more likely to succeed, as illustrated in Fig.  2 A, which shows firms with three or more founders are more than twice as likely to succeed than solo-founded startups. This finding is consistent with investors’ advice to founders and previous studies 46 . We also noted that some personality types of founders increase the probability of success more than others, as shown in SI section  A.6 (Extended Data Figures  16 and 17 ). Also, we note that gender differences play out in the distribution of personality facets: successful female founders and successful male founders show facet scores that are more similar to each other than are non-successful female founders to non-successful male founders (see Extended Data Figure  18 ).

The Ensemble Theory of Team-Level Factors of Startup Success. ( A ) Having a larger founder team elevates the chances of success. This can be due to multiple reasons, e.g., a more extensive network or knowledge base but also personality diversity. ( B ) We show that joint personality combinations of founders are significantly related to higher chances of success. This is because it takes more than one founder to cover all beneficial personality traits that ‘breed’ success. ( C ) In our multifactor model, we show that firms with diverse and specific combinations of types of founders have significantly higher odds of success.

Access to more extensive networks and capital could explain the benefits of having more founders. Still, as we find here, it also offers a greater diversity of combined personalities, naturally providing a broader range of maximum traits. So, for example, one founder may be more open and adventurous, and another could be highly agreeable and trustworthy, thus, potentially complementing each other’s particular strengths associated with startup success.

The benefits of larger and more personality-diverse foundation teams can be seen in the apparent differences between successful and unsuccessful firms based on their combined Big Five personality team footprints, as illustrated in Fig.  2 B. Here, maximum values for each Big Five trait of a startup’s co-founders are mapped; stratified by successful and non-successful companies. Founder teams of successful startups tend to score higher on Openness, Conscientiousness, Extraversion, and Agreeableness.

When examining the combinations of founders with different personality types, we find that some ensembles of personalities were significantly correlated with greater chances of startup success—while controlling for other variables in the model—as shown in Fig.  2 C (for more details on the modelling, the predictive performance and the coefficient estimates of the final model, see Extended Data Figures  19 , 20 , and 21 in SI section  A.6 ).

Three combinations of trio-founder companies were more than twice as likely to succeed than other combinations, namely teams with (1) a Leader and two Developers , (2) an Operator and two Developers , and (3) an Expert/Engineer , Leader and Developer . To illustrate the potential mechanisms on how personality traits might influence the success of startups, we provide some examples of well-known, successful startup founders and their characteristic personality traits in Extended Data Figure  22 .

Startups are one of the key mechanisms for brilliant ideas to become solutions to some of the world’s most challenging economic and social problems. Examples include the Google search algorithm, disability technology startup Fingerwork’s touchscreen technology that became the basis of the Apple iPhone, or the Biontech mRNA technology that powered Pfizer’s COVID-19 vaccine.

We have shown that founders’ personalities and the combination of personalities in the founding team of a startup have a material and significant impact on its likelihood of success. We have also shown that successful startup founders’ personality traits are significantly different from those of successful employees—so much so that a simple predictor can be trained to distinguish between employees and entrepreneurs with more than 80% accuracy using personality trait data alone.

Just as occupation-personality maps derived from data can provide career guidance tools, so too can data on successful entrepreneurs’ personality traits help people decide whether becoming a founder may be a good choice for them.

We have learnt through this research that there is not one type of ideal ’entrepreneurial’ personality but six different types. Many successful startups have multiple co-founders with a combination of these different personality types.

To a large extent, founding a startup is a team sport; therefore, diversity and complementarity of personalities matter in the foundation team. It has an outsized impact on the company’s likelihood of success. While all startups are high risk, the risk becomes lower with more founders, particularly if they have distinct personality traits.

Our work demonstrates the benefits of personality diversity among the founding team of startups. Greater awareness of this novel form of diversity may help create more resilient startups capable of more significant innovation and impact.

The data-driven research approach presented here comes with certain methodological limitations. The principal data sources of this study—Crunchbase and Twitter—are extensive and comprehensive, but there are characterised by some known and likely sample biases.

Crunchbase is the principal public chronicle of venture capital funding. So, there is some likely sample bias toward: (1) Startup companies that are funded externally: self-funded or bootstrapped companies are less likely to be represented in Crunchbase; (2) technology companies, as that is Crunchbase’s roots; (3) multi-founder companies; (4) male founders: while the representation of female founders is now double that of the mid-2000s, women still represent less than 25% of the sample; (5) companies that succeed: companies that fail, especially those that fail early, are likely to be less represented in the data.

Samples were also limited to those founders who are active on Twitter, which adds additional selection biases. For example, Twitter users typically are younger, more educated and have a higher median income 47 . Another limitation of our approach is the potentially biased presentation of a person’s digital identity on social media, which is the basis for identifying personality traits. For example, recent research suggests that the language and emotional tone used by entrepreneurs in social media can be affected by events such as business failure 48 , which might complicate the personality trait inference.

In addition to sampling biases within the data, there are also significant historical biases in startup culture. For many aspects of the entrepreneurship ecosystem, women, for example, are at a disadvantage 49 . Male-founded companies have historically dominated most startup ecosystems worldwide, representing the majority of founders and the overwhelming majority of venture capital investors. As a result, startups with women have historically attracted significantly fewer funds 50 , in part due to the male bias among venture investors, although this is now changing, albeit slowly 51 .

The research presented here provides quantitative evidence for the relevance of personality types and the diversity of personalities in startups. At the same time, it brings up other questions on how personality traits are related to other factors associated with success, such as:

Will the recent growing focus on promoting and investing in female founders change the nature, composition and dynamics of startups and their personalities leading to a more diverse personality landscape in startups?

Will the growth of startups outside of the United States change what success looks like to investors and hence the role of different personality traits and their association to diverse success metrics?

Many of today’s most renowned entrepreneurs are either Baby Boomers (such as Gates, Branson, Bloomberg) or Generation Xers (such as Benioff, Cannon-Brookes, Musk). However, as we can see, personality is both a predictor and driver of success in entrepreneurship. Will generation-wide differences in personality and outlook affect startups and their success?

Moreover, the findings shown here have natural extensions and applications beyond startups, such as for new projects within large established companies. While not technically startups, many large enterprises and industries such as construction, engineering and the film industry rely on forming new project-based, cross-functional teams that are often new ventures and share many characteristics of startups.

There is also potential for extending this research in other settings in government, NGOs, and within the research community. In scientific research, for example, team diversity in terms of age, ethnicity and gender has been shown to be predictive of impact, and personality diversity may be another critical dimension 52 .

Another extension of the study could investigate the development of the language used by startup founders on social media over time. Such an extension could investigate whether the language (and inferred psychological characteristics) change as the entrepreneurs’ ventures go through major business events such as foundation, funding, or exit.

Overall, this study demonstrates, first, that startup founders have significantly different personalities than employees. Secondly, besides firm-level factors, which are known to influence firm success, we show that a range of founder-level factors, notably the character traits of its founders, significantly impact a startup’s likelihood of success. Lastly, we looked at team-level factors. We discovered in a multifactor analysis that personality-diverse teams have the most considerable impact on the probability of a startup’s success, underlining the importance of personality diversity as a relevant factor of team performance and success.

Data sources

Entrepreneurs dataset.

Data about the founders of startups were collected from Crunchbase (Table  2 ), an open reference platform for business information about private and public companies, primarily early-stage startups. It is one of the largest and most comprehensive data sets of its kind and has been used in over 100 peer-reviewed research articles about economic and managerial research.

Crunchbase contains data on over two million companies - mainly startup companies and the companies who partner with them, acquire them and invest in them, as well as profiles on well over one million individuals active in the entrepreneurial ecosystem worldwide from over 200 countries and spans. Crunchbase started in the technology startup space, and it now covers all sectors, specifically focusing on entrepreneurship, investment and high-growth companies.

While Crunchbase contains data on over one million individuals in the entrepreneurial ecosystem, some are not entrepreneurs or startup founders but play other roles, such as investors, lawyers or executives at companies that acquire startups. To create a subset of only entrepreneurs, we selected a subset of 32,732 who self-identify as founders and co-founders (by job title) and who are also publicly active on the social media platform Twitter. We also removed those who also are venture capitalists to distinguish between investors and founders.

We selected founders active on Twitter to be able to use natural language processing to infer their Big Five personality features using an open-vocabulary approach shown to be accurate in the previous research by analysing users’ unstructured text, such as Twitter posts in our case. For this project, as with previous research 20 , we employed a commercial service, IBM Watson Personality Insight, to infer personality facets. This service provides raw scores and percentile scores of Big Five Domains (Openness, Conscientiousness, Extraversion, Agreeableness and Emotional Stability) and the corresponding 30 subdomains or facets. In addition, the public content of Twitter posts was collected, and there are 32,732 profiles that each had enough Twitter posts (more than 150 words) to get relatively accurate personality scores (less than 12.7% Average Mean Absolute Error).

The entrepreneurs’ dataset is analysed in combination with other data about the companies they founded to explore questions about the nature and patterns of personality traits of entrepreneurs and the relationships between these patterns and company success.

For the multifactor analysis, we further filtered the data in several preparatory steps for the success prediction modelling (for more details, see SI section  A.5 ). In particular, we removed data points with missing values (Extended Data Fig.  13 ) and kept only companies in the data that were founded from 1990 onward to ensure consistency with previous research 32 (see Extended Data Fig.  14 ). After cleaning, filtering and pre-processing the data, we ended up with data from 25,214 founders who founded 21,187 startup companies to be used in the multifactor analysis. Of those, 3442 startups in the data were successful, 2362 in the first seven years after they were founded (see Extended Data Figure  15 for more details).

Entrepreneurs and employees dataset

To investigate whether startup founders show personality traits that are similar or different from the population at large (i. e. the entrepreneurs vs employees sub-analysis shown in Fig.  1 A and B), we filtered the entrepreneurs’ data further: we reduced the sample to those founders of companies, which attracted more than US$100k in investment to create a reference set of successful entrepreneurs (n \(=\) 4400).

To create a control group of employees who are not also entrepreneurs or very unlikely to be of have been entrepreneurs, we leveraged the fact that while some occupational titles like CEO, CTO and Public Speaker are commonly shared by founders and co-founders, some others such as Cashier , Zoologist and Detective very rarely co-occur seem to be founders or co-founders. To illustrate, many company founders also adopt regular occupation titles such as CEO or CTO. Many founders will be Founder and CEO or Co-founder and CTO. While founders are often CEOs or CTOs, the reverse is not necessarily true, as many CEOs are professional executives that were not involved in the establishment or ownership of the firm.

Using data from LinkedIn, we created an Entrepreneurial Occupation Index (EOI) based on the ratio of entrepreneurs for each of the 624 occupations used in a previous study of occupation-personality fit 44 . It was calculated based on the percentage of all people working in the occupation from LinkedIn compared to those who shared the title Founder or Co-founder (See SI section  A.2 for more details). A reference set of employees (n=6685) was then selected across the 112 different occupations with the lowest propensity for entrepreneurship (less than 0.5% EOI) from a large corpus of Twitter users with known occupations, which is also drawn from the previous occupational-personality fit study 44 .

These two data sets were used to test whether it may be possible to distinguish successful entrepreneurs from successful employees based on the different patterns of personality traits alone.

Hierarchical clustering

We applied several clustering techniques and tests to the personality vectors of the entrepreneurs’ data set to determine if there are natural clusters and, if so, how many are the optimum number.

Firstly, to determine if there is a natural typology to founder personalities, we applied the Hopkins statistic—a statistical test we used to answer whether the entrepreneurs’ dataset contains inherent clusters. It measures the clustering tendency based on the ratio of the sum of distances of real points within a sample of the entrepreneurs’ dataset to their nearest neighbours and the sum of distances of randomly selected artificial points from a simulated uniform distribution to their nearest neighbours in the real entrepreneurs’ dataset. The ratio measures the difference between the entrepreneurs’ data distribution and the simulated uniform distribution, which tests the randomness of the data. The range of Hopkins statistics is from 0 to 1. The scores are close to 0, 0.5 and 1, respectively, indicating whether the dataset is uniformly distributed, randomly distributed or highly clustered.

To cluster the founders by personality facets, we used Agglomerative Hierarchical Clustering (AHC)—a bottom-up approach that treats an individual data point as a singleton cluster and then iteratively merges pairs of clusters until all data points are included in the single big collection. Ward’s linkage method is used to choose the pair of groups for minimising the increase in the within-cluster variance after combining. AHC was widely applied to clustering analysis since a tree hierarchy output is more informative and interpretable than K-means. Dendrograms were used to visualise the hierarchy to provide the perspective of the optimal number of clusters. The heights of the dendrogram represent the distance between groups, with lower heights representing more similar groups of observations. A horizontal line through the dendrogram was drawn to distinguish the number of significantly different clusters with higher heights. However, as it is not possible to determine the optimum number of clusters from the dendrogram, we applied other clustering performance metrics to analyse the optimal number of groups.

A range of Clustering performance metrics were used to help determine the optimal number of clusters in the dataset after an apparent clustering tendency was confirmed. The following metrics were implemented to evaluate the differences between within-cluster and between-cluster distances comprehensively: Dunn Index, Calinski-Harabasz Index, Davies-Bouldin Index and Silhouette Index. The Dunn Index measures the ratio of the minimum inter-cluster separation and the maximum intra-cluster diameter. At the same time, the Calinski-Harabasz Index improves the measurement of the Dunn Index by calculating the ratio of the average sum of squared dispersion of inter-cluster and intra-cluster. The Davies-Bouldin Index simplifies the process by treating each cluster individually. It compares the sum of the average distance among intra-cluster data points to the cluster centre of two separate groups with the distance between their centre points. Finally, the Silhouette Index is the overall average of the silhouette coefficients for each sample. The coefficient measures the similarity of the data point to its cluster compared with the other groups. Higher scores of the Dunn, Calinski-Harabasz and Silhouette Index and a lower score of the Davies-Bouldin Index indicate better clustering configuration.

Classification modelling

Classification algorithms.

To obtain a comprehensive and robust conclusion in the analysis predicting whether a given set of personality traits corresponds to an entrepreneur or an employee, we explored the following classifiers: Naïve Bayes, Elastic Net regularisation, Support Vector Machine, Random Forest, Gradient Boosting and Stacked Ensemble. The Naïve Bayes classifier is a probabilistic algorithm based on Bayes’ theorem with assumptions of independent features and equiprobable classes. Compared with other more complex classifiers, it saves computing time for large datasets and performs better if the assumptions hold. However, in the real world, those assumptions are generally violated. Elastic Net regularisation combines the penalties of Lasso and Ridge to regularise the Logistic classifier. It eliminates the limitation of multicollinearity in the Lasso method and improves the limitation of feature selection in the Ridge method. Even though Elastic Net is as simple as the Naïve Bayes classifier, it is more time-consuming. The Support Vector Machine (SVM) aims to find the ideal line or hyperplane to separate successful entrepreneurs and employees in this study. The dividing line can be non-linear based on a non-linear kernel, such as the Radial Basis Function Kernel. Therefore, it performs well on high-dimensional data while the ’right’ kernel selection needs to be tuned. Random Forest (RF) and Gradient Boosting Trees (GBT) are ensembles of decision trees. All trees are trained independently and simultaneously in RF, while a new tree is trained each time and corrected by previously trained trees in GBT. RF is a more robust and straightforward model since it does not have many hyperparameters to tune. GBT optimises the objective function and learns a more accurate model since there is a successive learning and correction process. Stacked Ensemble combines all existing classifiers through a Logistic Regression. Better than bagging with only variance reduction and boosting with only bias reduction, the ensemble leverages the benefit of model diversity with both lower variance and bias. All the above classification algorithms distinguish successful entrepreneurs and employees based on the personality matrix.

Evaluation metrics

A range of evaluation metrics comprehensively explains the performance of a classification prediction. The most straightforward metric is accuracy, which measures the overall portion of correct predictions. It will mislead the performance of an imbalanced dataset. The F1 score is better than accuracy by combining precision and recall and considering the False Negatives and False Positives. Specificity measures the proportion of detecting the true negative rate that correctly identifies employees, while Positive Predictive Value (PPV) calculates the probability of accurately predicting successful entrepreneurs. Area Under the Receiver Operating Characteristic Curve (AUROC) determines the capability of the algorithm to distinguish between successful entrepreneurs and employees. A higher value means the classifier performs better on separating the classes.

Feature importance

To further understand and interpret the classifier, it is critical to identify variables with significant predictive power on the target. Feature importance of tree-based models measures Gini importance scores for all predictors, which evaluate the overall impact of the model after cutting off the specific feature. The measurements consider all interactions among features. However, it does not provide insights into the directions of impacts since the importance only indicates the ability to distinguish different classes.

Statistical analysis

T-test, Cohen’s D and two-sample Kolmogorov-Smirnov test are introduced to explore how the mean values and distributions of personality facets between entrepreneurs and employees differ. The T-test is applied to determine whether the mean of personality facets of two group samples are significantly different from one another or not. The facets with significant differences detected by the hypothesis testing are critical to separate the two groups. Cohen’s d is to measure the effect size of the results of the previous t-test, which is the ratio of the mean difference to the pooled standard deviation. A larger Cohen’s d score indicates that the mean difference is greater than the variability of the whole sample. Moreover, it is interesting to check whether the two groups’ personality facets’ probability distributions are from the same distribution through the two-sample Kolmogorov-Smirnov test. There is no assumption about the distributions, but the test is sensitive to deviations near the centre rather than the tail.

Privacy and ethics

The focus of this research is to provide high-level insights about groups of startups, founders and types of founder teams rather than on specific individuals or companies. While we used unit record data from the publicly available data of company profiles from Crunchbase , we removed all identifiers from the underlying data on individual companies and founders and generated aggregate results, which formed the basis for our analysis and conclusions.

Data availability

A dataset which includes only aggregated statistics about the success of startups and the factors that influence is released as part of this research. Underlying data for all figures and the code to reproduce them are available on GitHub: https://github.com/Braesemann/FounderPersonalities . Please contact Fabian Braesemann ( [email protected] ) in case you have any further questions.

Change history

07 may 2024.

A Correction to this paper has been published: https://doi.org/10.1038/s41598-024-61082-7

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Acknowledgements

We thank Gary Brewer from BuiltWith ; Leni Mayo from Influx , Rachel Slattery from TeamSlatts and Daniel Petre from AirTree Ventures for their ongoing generosity and insights about startups, founders and venture investments. We also thank Tim Li from Crunchbase for advice and liaison regarding data on startups and Richard Slatter for advice and referrals in Twitter .

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Melbourne Graduate School of Education, The University of Melbourne, Parkville, VIC, Australia

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Contributions

All authors designed research; All authors analysed data and undertook investigation; F.B. and F.S. led multi-factor analysis; P.M., X.G. and M.A.R. led the founder/employee prediction; M.L.K. led personality insights; X.G. collected and tabulated the data; X.G., F.B., and F.S. created figures; X.G. created final art, and all authors wrote the paper.

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Correspondence to Fabian Braesemann .

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The original online version of this Article was revised: The Data Availability section in the original version of this Article was incomplete, the link to the GitHub repository was omitted. Full information regarding the corrections made can be found in the correction for this Article.

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McCarthy, P.X., Gong, X., Braesemann, F. et al. The impact of founder personalities on startup success. Sci Rep 13 , 17200 (2023). https://doi.org/10.1038/s41598-023-41980-y

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Modular, scalable hardware architecture for a quantum computer

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Quantum computers hold the promise of being able to quickly solve extremely complex problems that might take the world’s most powerful supercomputer decades to crack.

But achieving that performance involves building a system with millions of interconnected building blocks called qubits. Making and controlling so many qubits in a hardware architecture is an enormous challenge that scientists around the world are striving to meet.

Toward this goal, researchers at MIT and MITRE have demonstrated a scalable, modular hardware platform that integrates thousands of interconnected qubits onto a customized integrated circuit. This “quantum-system-on-chip” (QSoC) architecture enables the researchers to precisely tune and control a dense array of qubits. Multiple chips could be connected using optical networking to create a large-scale quantum communication network.

By tuning qubits across 11 frequency channels, this QSoC architecture allows for a new proposed protocol of “entanglement multiplexing” for large-scale quantum computing.

The team spent years perfecting an intricate process for manufacturing two-dimensional arrays of atom-sized qubit microchiplets and transferring thousands of them onto a carefully prepared complementary metal-oxide semiconductor (CMOS) chip. This transfer can be performed in a single step.

“We will need a large number of qubits, and great control over them, to really leverage the power of a quantum system and make it useful. We are proposing a brand new architecture and a fabrication technology that can support the scalability requirements of a hardware system for a quantum computer,” says Linsen Li, an electrical engineering and computer science (EECS) graduate student and lead author of a paper on this architecture.

Li’s co-authors include Ruonan Han, an associate professor in EECS, leader of the Terahertz Integrated Electronics Group, and member of the Research Laboratory of Electronics (RLE); senior author Dirk Englund, professor of EECS, principal investigator of the Quantum Photonics and Artificial Intelligence Group and of RLE; as well as others at MIT, Cornell University, the Delft Institute of Technology, the U.S. Army Research Laboratory, and the MITRE Corporation. The paper appears today in Nature .

Diamond microchiplets

While there are many types of qubits, the researchers chose to use diamond color centers because of their scalability advantages. They previously used such qubits to produce integrated quantum chips with photonic circuitry.

Qubits made from diamond color centers are “artificial atoms” that carry quantum information. Because diamond color centers are solid-state systems, the qubit manufacturing is compatible with modern semiconductor fabrication processes. They are also compact and have relatively long coherence times, which refers to the amount of time a qubit’s state remains stable, due to the clean environment provided by the diamond material.

In addition, diamond color centers have photonic interfaces which allows them to be remotely entangled, or connected, with other qubits that aren’t adjacent to them.

“The conventional assumption in the field is that the inhomogeneity of the diamond color center is a drawback compared to identical quantum memory like ions and neutral atoms. However, we turn this challenge into an advantage by embracing the diversity of the artificial atoms: Each atom has its own spectral frequency. This allows us to communicate with individual atoms by voltage tuning them into resonance with a laser, much like tuning the dial on a tiny radio,” says Englund.

This is especially difficult because the researchers must achieve this at a large scale to compensate for the qubit inhomogeneity in a large system.

To communicate across qubits, they need to have multiple such “quantum radios” dialed into the same channel. Achieving this condition becomes near-certain when scaling to thousands of qubits. To this end, the researchers surmounted that challenge by integrating a large array of diamond color center qubits onto a CMOS chip which provides the control dials. The chip can be incorporated with built-in digital logic that rapidly and automatically reconfigures the voltages, enabling the qubits to reach full connectivity.

“This compensates for the in-homogenous nature of the system. With the CMOS platform, we can quickly and dynamically tune all the qubit frequencies,” Li explains.

Lock-and-release fabrication

To build this QSoC, the researchers developed a fabrication process to transfer diamond color center “microchiplets” onto a CMOS backplane at a large scale.

They started by fabricating an array of diamond color center microchiplets from a solid block of diamond. They also designed and fabricated nanoscale optical antennas that enable more efficient collection of the photons emitted by these color center qubits in free space.

Then, they designed and mapped out the chip from the semiconductor foundry. Working in the MIT.nano cleanroom, they post-processed a CMOS chip to add microscale sockets that match up with the diamond microchiplet array.

They built an in-house transfer setup in the lab and applied a lock-and-release process to integrate the two layers by locking the diamond microchiplets into the sockets on the CMOS chip. Since the diamond microchiplets are weakly bonded to the diamond surface, when they release the bulk diamond horizontally, the microchiplets stay in the sockets.

“Because we can control the fabrication of both the diamond and the CMOS chip, we can make a complementary pattern. In this way, we can transfer thousands of diamond chiplets into their corresponding sockets all at the same time,” Li says.

The researchers demonstrated a 500-micron by 500-micron area transfer for an array with 1,024 diamond nanoantennas, but they could use larger diamond arrays and a larger CMOS chip to further scale up the system. In fact, they found that with more qubits, tuning the frequencies actually requires less voltage for this architecture.

“In this case, if you have more qubits, our architecture will work even better,” Li says.

The team tested many nanostructures before they determined the ideal microchiplet array for the lock-and-release process. However, making quantum microchiplets is no easy task, and the process took years to perfect.

“We have iterated and developed the recipe to fabricate these diamond nanostructures in MIT cleanroom, but it is a very complicated process. It took 19 steps of nanofabrication to get the diamond quantum microchiplets, and the steps were not straightforward,” he adds.

Alongside their QSoC, the researchers developed an approach to characterize the system and measure its performance on a large scale. To do this, they built a custom cryo-optical metrology setup.

Using this technique, they demonstrated an entire chip with over 4,000 qubits that could be tuned to the same frequency while maintaining their spin and optical properties. They also built a digital twin simulation that connects the experiment with digitized modeling, which helps them understand the root causes of the observed phenomenon and determine how to efficiently implement the architecture.

In the future, the researchers could boost the performance of their system by refining the materials they used to make qubits or developing more precise control processes. They could also apply this architecture to other solid-state quantum systems.

This work was supported by the MITRE Corporation Quantum Moonshot Program, the U.S. National Science Foundation, the U.S. Army Research Office, the Center for Quantum Networks, and the European Union’s Horizon 2020 Research and Innovation Program.

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How Science, Math, and Tech Can Propel Swimmers to New Heights

One hundred years ago, in the 1924 Paris Olympics, American Johnny Weissmuller won the men’s 100m freestyle with a time of 59 seconds. Nearly 100 years later in the most recent Olympics, the delayed 2020 Games in Tokyo, Caeleb Dressel took home the same event with a time that was 12 seconds faster than Weissmuller’s.  

Swimming times across the board have become much faster over the past century, a result of several factors, including innovations in training, recovery strategy, nutrition, and some equipment advances.  

One component in the improvement in swimming performances over the years is the role of biomechanics — that is, how swimmers optimize their stroke, whether it's the backstroke, breaststroke, butterfly, or freestyle.  

Swimmers for decades have experimented with different techniques to gain an edge over their competitors. But in more recent years, the application of mathematics and science principles as well as the use of wearable sensor technology in training regimens has allowed some athletes to elevate their performances to new heights, including members of the University of Virginia’s swim team.  

In a new research paper , a UVA professor who introduced these concepts and methods to the team and some of the swimmers who have embraced this novel approach to training lay out how the use of data is helping to transform how competitive swimmers become elite.

‘Swimming in Data’

Ken Ono thought his time working with swim teams was over. Ono — a UVA mathematics professor, professor of data science by courtesy, and STEM advisor to the University provost — had spent years working with competitive swimmers, first during his time at Emory University in Atlanta and then with other college teams, including Olympians, over the years.

However, he didn’t plan to continue that aspect of his work when he arrived at UVA in 2019. But after a meeting with Todd DeSorbo, who took over the UVA swim program in 2017, Ono soon found himself once again working closely with athletes, beginning his work as a consultant for the team during the 2020-21 season . The UVA women’s swim team would win their first of four consecutive national championships that year.  

“One of the things that I like quite a bit about this work is that swimming is crazy hard,” Ono said. “We were never meant to be swimmers, and it is both an athletic challenge as well as a scientific challenge — it has it all.”

Last fall, following a suggestion from DeSorbo, Ono offered a class that outlined the science-focused approach to improving swimming performances that had proven so successful at UVA, but he wanted to make sure there were no misconceptions about the seriousness of the material.

“We don’t want people thinking that it’s a cupcake course that’s offered for the swimmers,” Ono said.

So, Ono teamed up with UVA students Kate Douglass, August Lamb, and Will Tenpas, as well as MIT graduate student Jerry Lu who had worked with Ono and the UVA swim team while an undergraduate at the University, to produce a paper that covered the key elements of the class and Ono’s work with swimmers.  

Tenpas and Lamb both recently completed the residential master’s program at the School of Data Science as well as their careers as competitive collegiate swimmers. Douglass, who finished her UVA swim career in 2023 as one of the most decorated swimmers in NCAA history, is a graduate student in statistics at the University and is set to compete in the Paris Olympics after winning a bronze medal in the 2020 games.

The group drafted the paper, which they titled “Swimming in Data,” over the course of two months, and it was quickly accepted by The Mathematical Intelligencer. There, Ono said, it has become one of the most-read papers on a STEM subject since tracking began. In July, a version of the paper will also be published in Scientific American.  

“It seems to have taken off,” Ono said.

The impact of digital twins

After outlining the evolution of swimming over the past 100 years, the paper explains how an understanding of math and physics, combined with the use of technology to acquire individual-level data, can help maximize performances.  

Essential to understanding the scientific principles involved with the swimming stroke, the paper says, are Newton’s laws of motion. The laws — which cover inertia, the idea that acceleration depends on an object’s mass and the amount of force applied, and the principle that an action exerted by an object on another elicits an equal and opposite reaction — help simplify how one should think about the many biomechanical factors involved with swimming, according to Tenpas.

“There are all sorts of flexibility limitations. You have water moving at you, you have wakes, you have currents — it’s easy to kind of get paralyzed by the number of factors,” said Tenpas, who after four years at Duke, where he studied mechanical engineering, enrolled in UVA’s data science program and joined the swim team with a fifth year of eligibility.

“I think having Newton’s laws is nice as it gives you this baseline we can all agree on,” he added.  

It’s a way to understand pool mechanics given the counterintuitive motion swimmers must use to propel themselves forward, according to Ono.  

“The reason that we go to great extent to recall Newton’s laws of motion is so that we can break down the factors that matter when you test a swimmer,” he said.  

To conduct these tests, Ono and his team use sensors that can be placed on swimmers’ wrists, ankles, or backs to gather acceleration data, measured as inertial measurement units. That information is then used to generate what are called digital twins, which precisely replicate a swimmer’s movements.  

These twins reveal strengths and weaknesses, allowing Ono and the coaching staff to make recommendations on technique and strategy — such as how to reduce drag force, a swimmer’s true opponent — that will result in immediate improvement. In fact, through the analysis of data and the use of Newton’s laws, it is possible to make an accurate prediction about how much time a swimmer can save by making a given adjustment.

Lamb, who swam for UVA for five years while a computer science undergrad then as a data science master’s student, likened digital twins to a feature in the popular Nintendo game Mario Kart where you can race against a ghost version of yourself.  

“Being able to have this resource where you can test at one month and then spend a month or two making that adjustment and then test again and see what the difference is — it’s an incredibly valuable resource,” he said.  

To understand the potential of digital twins, one need only look at the example of Douglass, one of the co-authors, which is cited in the paper.

A flaw was identified in her head position in the 200m breaststroke. Using her digital twin, Ono and the coaching staff were able to quantify how much time she could save per streamline glide by making a modification, given her obvious talent and aerobic capacity. She did, and the results were remarkable. In November 2020, when her technique was tested, the 200m breaststroke wasn’t even on her event list. Three years later, she held the American record.

‘Everyone’s doing it now’

Swimming will be front and center in the national consciousness this summer. First, the U.S. Olympic Team Trials will be held in Indianapolis in June, leading up to the Paris Olympics in July and August, where DeSorbo, UVA’s coach who embraced Ono’s data-driven strategic advice, will lead the women’s team.  

Many aspiring swimmers will undoubtedly be watching over the coming weeks, wondering how they might realize their full athletic potential at whatever level that might be.  

For those who have access to technology and data about their technique, Tenpas encouraged young swimmers to take advantage.  

He noted the significant amount of time a swimmer must put in to reach the highest levels of the sport, estimating that he had been swimming six times per week since he was 12 years old.  

“If you’re going to put all of this work in, at least do it smart,” Tenpas said.  

At the same time, Lamb urged young swimmers who may not yet have access to this technology to not lose faith in their potential to improve.  

“While this is an incredibly useful tool to make improvements to your technique and to your stroke, it’s not the end all, be all,” he said.

“There are so many different ways to make improvements, and we’re hopeful that this will become more accessible as time goes on,” Lamb said of the data methods used at UVA.

As for where this is all going, with the rapidly expanding use and availability of data and wearable technology, Ono thinks his scientific approach to crafting swimming strategies will soon be the norm.  

“I think five years from now, our story won’t be a story. It’ll be, ‘Oh, everyone’s doing it now,’” he said. 

MSDS Student Profiles: August Lamb and Will Tenpas on Balancing Swimming and Graduate School

Ken Ono Talks About Using Data to Improve Swimmer Performance on CBS19 for “Inside The Numbers”

Data Science Master’s Students Tackle Diverse, Real-World Challenges in Capstone Projects

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