research article social sciences

Social Science Research: Principles, Methods and Practices - (Revised edition)

(43 reviews)

Anol Bhattacherjee, University of South Florida

ISBN 13: 9781475146127

Publisher: University of Southern Queensland

Language: English

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Reviewed by Kelle DeBoth Foust, Associate Professor, Cleveland State University on 6/22/23

Comprehensiveness rating: 5 see less

The text really seems to do as it claims; provides the basic overview of the research material needed for graduate students without a lot of other “fluff.” It’s written very clearly, easy to understand and many figures and charts that enhance learning. It covers the majority of the topics that I need it to cover for OTH 740/Research I, at about the level of detail that the students should be able to digest. In particular, I like the sections on survey research, experimental research and that it covers quantitative and qualitative analyses.

Content Accuracy rating: 4

As far as I can tell reading through it, the content is accurate and unbiased (will be able to review further once actually implemented in the intended course).

Relevance/Longevity rating: 4

The content is current at least regarding how we continue to teach and use it in our field. Some of the references are a little outdated, although not much has changed in this world in recent years. I also recognize I can pull more recent literature in order to make the examples up to date and relevant for my particular students.

Clarity rating: 5

This book is written very clearly. I feel that the diagrams really help to add and make sense of higher level concepts that students may struggle with. Concepts that are challenging are recognized as such within the text, with appropriate examples that enhance clarity (will be able to review further once actually implemented in the intended course)

Consistency rating: 5

Yes, the text appears to be internally consistent in terms of terminology and framework.

Modularity rating: 5

The text is easily and readily divisible into smaller reading sections that can be assigned at different points within the course (i.e., enormous blocks of text without subheadings should be avoided). The text should not be overly self-referential, and should be easily reorganized and realigned with various subunits of a course without presenting much disruption to the reader. – Yes. The division of the content makes sense, and how smaller modules are paired (e.g., qualitative and quantitative analysis paired back to back) is logical to facilitate learning.

Organization/Structure/Flow rating: 5

The text and chapters are laid out in an order that makes sense and provides good flow and continuity between the concepts and analytical applications. In particular, I like how research is introduced, moving into research design and then analysis all within the same text. Will make this more manageable for students.

Interface rating: 5

The text is free of significant interface issues, including navigation problems, distortion of images/charts, and any other display features that may distract or confuse the reader. – Very well put together, no issues with the interface. I would consider this to be very user/student friendly. In particular, the authors made a point to keep it “short and sweet” so students should not be intimidated by the length of the chapters (which is excellent for helping to convince the students to actually read them).

Grammatical Errors rating: 5

The text contains no grammatical errors. – None detected.

Cultural Relevance rating: 5

The text is not culturally insensitive or offensive in any way. It should make use of examples that are inclusive of a variety of races, ethnicities, and backgrounds. – No offensive content noted, the majority of the examples used do not have cultural significance and therefore the amount of diversity is sufficient.

This review was written based on a preliminary review of the text prior to use and implementation within the intended course. I will update the review if it significantly differs once students have used it for their course study.

Reviewed by Ingrid Carter, Professor, Metropolitan State University of Denver on 4/14/23

The textbook includes many of the important elements of a foundational social science research course. A key element of the course I teach which is not included in the text is how to search for literature to inform the research, how to synthesize... read more

Comprehensiveness rating: 4 see less

Content Accuracy rating: 3

The content appears to be mostly accurate and unbiased. There is a large emphasis on positivist approaches, and more post-positivist and innovative research approaches should be added to the content.

The text is relevant to foundational/introductory social science research courses. As mentioned previously, broader and more diverse perspectives of research are missing.

Clarity rating: 4

The content is presented clearly.

Consistency rating: 4

The text is presented with a consistent framework and format. The variety of frameworks included could be greater, with at minimum a presentation of different research paradigms and ideally with discussion or questions to grapple with related to various research paradigms and approaches.

As the author indicates, the textbook consists of 16 chapters which can be used in a 16-week semester. These can be easily assigned for weekly readings.

The textbook is well-organized.

Interface rating: 4

The interface is relatively clear

No grammatical errors were found in my initial review. I have not yet used the textbook for the course I am teaching, and therefore have not reviewed the textbook page by page nor line by line.

Cultural Relevance rating: 3

More diverse and culturally relevant example to a diverse audience could be embedded. I did not encounter offensive material.

Reviewed by Sanaa Riaz, Associate Professor, Metropolitan State University of Denver on 3/27/23

Comprehensiveness rating: 3 see less

While not meant for advanced graduate and doctoral students, this text is an excellent introductory resource for learning about paradigms in research methods and data analysis and prepares the learner to begin writing a successful research project proposal. The text largely privileges the scientific method and labels diverse social science research methods as such. However, the preparatory considerations in beginning social science research have been discussed. The book contains important terms in bold to guide a beginner reader as well as sample syllabi for incorporating it at the graduate level. However, the text could be made more comprehensive with the inclusion of an effective index and/or glossary.

Content Accuracy rating: 5

The text is a quick guide to considerations and terminologies used in social science research. The content is accurate, error-free and unbiased.

The text provides a basic introduction to research methods in the social sciences. Updates in social science inquiry with respect to social media and popular culture platforms and mixed methods research should be easy to incorporate.

The text has been written from the point of view of a non-expert. It is free of technical jargon and is meant to provide the essentials of social science inquiry and research considerations.

Consistency rating: 3

The text is internally consistent in terms of terminology within a chapter section. However, it is strongly recommended that the framework is revisited for chapters discussing qualitative research methods and approaches. Qualitative data analysis has not been explored in depth and the basic framework for Chapter 13 will need to be substantially expanded to provide for a smoother transition from a discussion on grounded theory to content analysis and hermeneutic analysis and to incorporate information on other analyses undertaken in qualitative research.

Chapters and sections in the text can be easily reorganized and assigned as per needs of the instructor and the course without causing disruption to the reader.

Organization/Structure/Flow rating: 3

Chapter sections of the book covering qualitative research are not presented in a logical manner. It is highly recommended that the readers are told about the place of exploratory and other research in social science research inquiry, rather than labeling them as scientific research. Moreover, mixed methods and qualitative visual and social media platform research needs to be discussed. The book overall shies away from delving into approaches and methods in non-empirical research in the social sciences.

The text is easy to navigate. All words, sections and tables are easily searchable.

The book is free of grammatical errors.

The text does not contain any culturally insensitive information as there are hardly any research project examples incorporated.

Incorporating examples and case studies across social science disciplines (after introducing the disciplines in which social science research is employed in the first chapter) would allow readers to see the applicability of one social science research approach, method and data analysis over another based on the research project focus.

Reviewed by Cahit Kaya, ASSISTANT PROFESSOR, University of Texas Rio Grande Valley on 10/17/22

I LIKE THE FIGURE EXPLAINING RELIABILITY AND VALIDITY ON PAGE 55. read more

Comprehensiveness rating: 2 see less

I LIKE THE FIGURE EXPLAINING RELIABILITY AND VALIDITY ON PAGE 55.

IT SEEMED ACCURATE

Relevance/Longevity rating: 3

IT IS RELEVANT

IT IS CLEAR

IT IS CONSISTENT

Modularity rating: 3

IT NEEDS MORE MODULES

Organization/Structure/Flow rating: 2

IT CAN BE OGRANIZED BETTER

YES BUT EVEN THOUGH IT CAN BE IMPROVED

Grammatical Errors rating: 4

I DID NOT SEE IT

MORE CULTURAL DIVERSE EXAMPLES CAN BE GIVEN

Reviewed by Dawn DeVries, Associate Professor, Grand Valley State University on 12/9/21

The text provides a complete summary of the research process. While discussions are brief and concise, the text addresses the main issues and processes providing an overview and general understanding of the research process for social science fields. Two areas could be more in-depth, specifically the IRB discussion and the chapter on surveys. Information provided is accurate and succinct as the author intended, providing a comprehensive overview of the research process.

The content is accurate and presented in an objective manner. There was no perception of bias or conflict that would impact accuracy. The chapters offer a variety of examples, inclusive of a variety of social science fields.

Written in 2012, the information remains relevant with few areas that would ever need to change. The research process and research methods stay fairly consistent with little variation; thus, the text would not need regular updating. Updates, if and when needed, would be easy to implement due to the concise and objective writing and the logical organization of the textbook. One area needing updating (or that instructors would need to supplement) is Chapter 9 on Survey Research. The chapter refers to mail surveys, which in 2021, are almost obsolete. Little is presented or discussed on electronic surveys, survey platforms, or the use of social media in recruitment, survey distribution or every survey completion. Furthermore, there is no mention of the ethical issues related to social media research.

Key terminology is bolded with the definition following, making it easy to identify. Definitions are clear and adequate to facilitate understanding of the concepts and terms. The text presents the research process in a logical and understandable way using scaffolding.

The chapter structure, framework, and style are consistent.

Modularity rating: 4

The chapters provide easily divisible readings of 8-10 pages. The chapters are ordered in a logical fashion and flow easily, yet they could be rearranged to fit instructor preferences for order. Chapters are concise, allowing the combination of multiple chapters for a week’s reading if needed. The text is designed for a 16-week semester, but again, because the chapters are not long, several chapters could be read as one assignment. It would be difficult to reduce chapter readings (say, using only 5 pages of the chapter) because of the conciseness of the information and the shortness of the chapters.

The text is logical and has flow. It starts general (with How to Think Like a Researcher) and builds to specific, more detailed content (Inferential Statistics).

There are no observed problems with the interface of the text. Images used are clear and display without difficulty. No hyperlinks are used.

No observed issues or concerns related to grammar or mechanics.

No concerns about inclusivity or offensiveness. The text is clear and concise, offering a variety of short examples specific to various social science professions.

The text reminds me of my Research Methods textbook from my doctoral program. It addresses the differences between scientific research and social science methods in a clear and concise manner. While it is an overview of the information, it is specific and concise enough for students who need to understand the research process but won’t be engaging in research as their full-time profession. Content is brief in a few areas as mentioned, which will allow the instructor to provide supplemental reading or lecture content specific to the university (i.e., IRB) or to the profession. As the author suggests, certain chapters could be skipped depending on the program. For example, chapters 13 – 15 on statistics could easily be omitted if the program has a research statistics course. A nice add is the sample syllabus for a doctoral program.

Reviewed by David Denton, Associate Professor, Seattle Pacific University on 5/3/21

I use this book with graduate students in education taking an initial course in education research. Dr. Bhattacherjee notes the book is organized for semesters with supplemental readings, as shown by the sample syllabus in the appendix. Nevertheless, I have found the book is excellent in meeting objectives for an introductory course in education research, though it is necessary to add education context and examples. Some of the course objectives I have developed from the textbook include i) distinguishing between questionnaire survey method and interview survey method and ii) summarizing criteria for developing effective questionnaire items, among many others. There are some sections that exceed student knowledge without some background in statistics (e.g. description of factor analysis) but omitting these sections as required reading is easy since there are many subheadings used to segment chapters.

Dr. Bhattacherjee has done an excellent job of clearly communicating the content with accuracy. For example, the textbook distinguishes between qualitative and quantitative analysis (rather than qualitative and quantitative research, an appropriate distinction). The textbook makes other distinctions in a way that helps students comprehend concepts (e.g. survey interview and survey questionnaire). At the same time, the textbook does not over-emphasize research methods or design, which might mislead students to think inflexibly about the topic.

Relevance/Longevity rating: 5

One of the advantages of the book, in my view, is that it will not become obsolete anytime soon. It addresses all major topics of interest for instructors needing to develop student background knowledge in social science research methodology. For example, some topics for which the book provides helpful structure include i) Thinking Like a Researcher, ii) The Research Process, iii) Research Design, iv) and Sampling. In addition, an instructor can easily supplement or provide subject-specific examples where needed since the book is thoroughly segmented by chapter and chapter subheadings.

Dr. Bhattacherjee does a fine job of defining terms concisely. I do not recall use of jargon, or if there are complicated terms, the text provides enough elaboration so that students can at least attain a conceptual understanding. In some instances, definitions are so concise that I find it necessary to elaborate with examples. This, however, is a part of instruction and would be done in any case.

The textbook is highly coherent, in my view. Similar to modularity, consistency is a strength. For example, chapters are grouped into four sections: Introduction to Research, Basics of Empirical Research, Data Collection, and Data Analysis. Further, chapters within major sections are sequential, such as chapters on Science and Scientific Research, followed by Thinking Like a Researchers, followed by The Research Process. In addition, content within chapters is consistent, such as Dr. Bhattacherjee’s logical progression of concepts: empiricism, to positivism, to forms of analysis (qualitative and quantitative), etc

Modularity is one of the clear strengths, again in my view. From a structural perspective, neither the chapters nor subsections are very long because Dr. Bhattacherjee writes concisely. Both chapters and subordinate subsections lend themselves to various kinds of divisions. For example, students in need of supplemental instruction on descriptive statistics, such as content about the normal distribution, can be assigned the subsection on Statistics of Sampling in chapter 8, followed by the subsection on Central tendency in chapter 14. Some non-sequential reading is required if students do not have any background in statistics, but this is not difficult to manage using page numbers or subheadings as reference.

Organization/Structure/Flow rating: 4

The textbook is well organized. Nevertheless, there are some sections that I found helpful to have students read out of sequence. For example, there is a short section at the end of chapter 5, Scale Reliability and Validity, which is perhaps best read after students cover correlation and normal distribution, dealt with in chapter 14. Again, I did not find it difficult to assign sections out of sequence using either page numbers or chapter subheadings as reference.

The textbook does not have interface issues. Chapter titles are hyperlinked within PDF copies to simplify navigation. Some may judge a few of the images as low resolution, but if this is a defect it is not one that interferes with communicating concepts, which is the purpose of the images.

There are a few minor grammatical errors in the 2nd edition, 2012. For example, on p. 126, Dr. Bhattacherjee notes “five female students” when the Chi-square table appears to show four. This is minor, but if students are new to reading Chi-square tables they may not detect the error and believe interpreting a Chi-square table is different than interpreting a typical data table.

The textbook presents appropriate information without prejudice or unfairness. As mentioned, instructors will likely need to include examples that are specific to their course objectives and student populations. For example, chapter 11. Case Research provides exemplars that focus on business and marketing domains. This seems entirely appropriate given Dr. Bhattacherjee’s research area. Instructors using the text for other domains, such as education research, will be interested in elaborating on concepts using examples specific to the needs of their students.

I greatly appreciate that Dr. Bhattacherjee has shared his book as an Open Textbook.

Reviewed by Elizabeth Moore, Associate Professor, University of Indianapolis on 4/24/21

In Chapter 5 on Research Design there isn't any discussion on how to improve content and statistical conclusion validity. There isn't a discussion of threats associated with the four types of validity. The chapter also does not present how the research design and threats to validity are interconnected. There is a lack of comprehensiveness in the presentation of qualitative research as qualitative research rigor is not addressed.

The content is accurate, error-free, and unbiased. I would like more examples focused on social sciences. Some of the examples are related to business/industry. There are many social science examples that could be used.

Many of the examples should be updated. With everything that is (has been) happening in the U.S. and world, there are many examples that can come from the social sciences. For example, there are several examples that could represent the concept of technostress, especially with many professionals having to move into online environments. Students would be more likely to read assigned chapters and understand the material presented if the examples were relevant to their profession.

The book is clear and has high readability. There are several accessibility issues in the document. This should be checked and fixed. There are 5 issues in the document, 4 in tables, 5 in alternative text, etc. Accessibility is a big issue right now. All documents have to be accessible to all students.

While there is consistency within the textbook, in some topics there is a lock of consistency in how some of the terms and material relate to what is actually used in social science disciplines. For example, in basic social science textbooks in chapters presenting an introduction to measurement of constructs, descriptive statistics that are unfamiliar and rarely used, such as geometric mean and harmonic mean, should not be introduced. This information is usually difficult for novice researchers to understand without adding more advanced descriptive statistics.

It is confusing as to why research validity is in Chapter 5 - Research Design. There is not a discussion of how different research types are affected by different types and threats of research validity. The title of Chapter 7 is misleading. The word "scale" is associated with scale of measurement. It would be better to use designing measurement tools/instruments in the chapter name since the types of validity and reliability discussed are related to creating and developing measurement tools/instruments. I also think Chapter 6 - Measurement of Construction should not come before Chapter 7 - Scale Reliability and Validity since measurement of constructs and scale reliability and validity are related to qualitative research.

I like the organization. It follows the current syllabus I use so it will require very little modifications.

As mentioned below, bookmarks would improve navigation of the pdf file. Also, having links from the table of contents to chapters would be helpful. Including some of the important subsections of the chapters would also improve navigation of the pdf version of the book. Tables and charts are helpful and supplement the text. Use of images would break-up the text.

None were noted.

Cultural Relevance rating: 4

See comments above about the relevancy of the material. While it is important to make sure a book is culturally sensitive and not offensive, it is also important to not ignore what is known about social injustices which are well-documented. Look at the lack of diversity in many professions and organizations, this is important to address.

It would be helpful if bookmarks were placed in the pdf version. While this is a social science textbook, it would be helpful to have subsection in Chapter 4 that introduces at least a couple of the main health behavior theories. These are commonly used by many researchers in social sciences.

Reviewed by Barbara Molargik-Fitch, Adjunct Professor, Trine University on 3/6/21

This textbook provides a nice overview of several topics related to social science specific research. read more

This textbook provides a nice overview of several topics related to social science specific research.

The textbook seems to be accurate and error free.

The text seems to be accurate, relevant, and useful.

The text is organized well and had a professional and academic tone while also understandable.

Text seemed to be internally consistent.

Text is easily divisible to be assigned as different points within the course.

Text is well organized.

The text is free of significant interface issues that would distract or confuse the reader.

I did not see grammatical errors.

I did not see any cultural issues.

I will be using this textbook for one of my classes. I am looking forward to using it. I think it has a lot to offer students looking to develop their research skills.

Reviewed by Kenneth Gentry, Assistant Professor, Radford University on 6/2/20

This text provides a great overview of core concepts relevant to health-science research. An overview of theory, designs, sampling, data collection, data analysis, and ethics are provided. It may be helpful in future editions to add additional content relating to qualitative research (i.e. additional types of designs, as well as how trustworthiness and rigor are addressed [for example, what specific steps can be taken by researchers to address dependability, credibility, confirmability and transferability]).

Information presented appears accurate and unbiased.

While much of the content is 'durable' (not likely to soon become obsolete), the relevance is dependent upon the focus of the instructor/course. For example, if the emphasis of the course will be on quantitative research, then this text is highly relevant, however, if the emphasis is on an equal balance between the traditions of qualitative and quantitative, then this text is slightly less relevant due to the more limited nature of its content in qualitative (in comparison to content on quantitative). That is not to say that this text does not address content relevant to qualitative research, however, it does so with decidedly less depth and breadth than quantitative.

While a subjective interpretation of clarity is highly dependent upon the reader, I found this text to strike a good balance between a scholarly, academic tone, and commonly-understood, easily-relatable descriptions of key concepts. There were times where I wish that the latter had been more so, however, considering the target audience of this text, I feel that the author struck a good balance. Occasionally, there were concepts that I anticipated would require additional clarification (beyond the reading) for my graduate students.

Overall, I found the text to be generally consistent in its approach to the content. Occasionally, there were instances when the flow made sense at the chapter level, however, content might have been spread between chapters (i.e. theory is discussed in Chapters 1, 2 and 4).

This ties in with my comments on consistency. Since some concepts are discussed in more than one place, it might be difficult to identify a single reading for a specific topic ... one might need to assign several readings from more than one chapter. However, having said that, I anticipate that those instances would be infrequent. On the whole, the text demonstrates a fairly good degree of modularity.

At the chapter level (i.e. main topics), and within each chapter, information appears well organized. It is the appearance of content in multiple places that was occasionally problematic for me as I read (i.e. when reading about reliability and validity, I questioned why the author did not discuss the types of reliability and validity ... I later found that content in a subsequent chapter).

Interface rating: 3

While images were viewable, many appeared 'pixelated'/'grainy' (low resolution). This was more of a cosmetic issue, and did not affect the overall interpretation of the image.

Overall, the content was grammatically strong.

Content was not culturally insensitive or offensive.

My sincere thanks to this author, and to the Open Textbook Library and Scholar Commons for this text. I truly appreciate the investment of resources that were invested. I just completed instructing 2 semester courses on research in a graduate health science degree program ... I plan to adopt this text the next time I am rotated into those courses again!

Reviewed by Wendy Bolyard, Clinical Assistant Professor, University of Colorado Denver on 4/30/20

This text presents all the topics, and more, that I cover in my master's-level research and analytic methods course. A glossary would be helpful as students often need to reference basic definitions as they learn these new concepts. I would have... read more

The concepts were presented accurately and often with citations.

The great thing about research methods is that the content ages well (does not change over time). The examples were relevant and should not make the text obsolete. Any instructor should be able to provide current, real-world examples to compare and contrast to those in the text. Although the sample syllabus if for a business class, I did not find the text to be relevant only to business students. The authors uses broad social science illustrations that cross disciplines. This text is definitely relevant to public affairs/public administration.

The text is well-written and provides clear yet concise context.

When students are learning a new language - research methods - they may be confused when definitions vary. Causality is explained with slightly different language which may be misunderstood by students.

One chapter includes a summary section. It would have been helpful to include a summary of key takeaways for each chapter, and perhaps include a list of key terms and definitions (since the text does not include a glossary).

The text follows the linear, systematic research process very well.

The font, size, and spacing varied in some sections. The images were a bit blurred.

A few typos, but otherwise well-written and very clear.

Culturally sensitive with relevant and inclusive cases provided.

I will be adopting this text to supplement other readings assigned in my master's-level research and analytic methods course. I appreciate the clear and helpful context it provides on key concepts that students must understand to become effective researchers. The text is comprehensive yet concise and would not overwhelm students.

Reviewed by Valerie Young, Associate Professor, Hanover College on 12/19/19

I really appreciate the broad focus and examples from social science fields. As a fellow social scientist from a high growth area (communication studies), I would appreciate even more breadth! I supplement with many field-specific resources, so this critique is very minor. An appropriate place and reference might be within the first chapter, under the heading Types of Scientific Research, to give a nod to some of the social science fields and the importance of interdisciplinary questions across disciplinary lines.

I did not find any errors in the content of the book. One critique is that the author rarely cites any sources for assertions or materials. I get the impression that the author is relying on "commonly known" ideas regarding research methods and processes, but I have to consistently remind my students to cite all non-original information, and that example is lacking in this text. As an example, regarding evaluating measurement scales for internal consistency, the author references commonly-accepted factor loadings (>.60) but does not reference or provide linked resources for readers to corroborate this or seek additional readings.

The text content is relevant and the author has taken care to provide relatively timeless sample research examples throughout. Some examples include areas of social and political interest (conflict, crime), business and marketing, and social psychology. The contents of the text are not dated and the author does a fantastic job of offering a variety of relevant examples so that readers of all backgrounds can relate to the content.

Incredibly clear and concise. Main ideas are clearly articulated in headings. Bullet point lists are used infrequently, but appropriately. The writing style is professional, academic in tone, yet relate-able. There is little, if any, discipline-specific references that a graduate student from any area of social sciences could not comprehend; however, this book is empirically-grounded and quantitatively focused. For our readers in fields with lower quantitative literacy, some of the terminology in chapters is better suited for students with basic statistical experience, some research methods or theory coursework completed.

This text is consistent and detailed in the use of interdisciplinary, social scientific terminology.

The layout of materials and the concise writing style contribute to an easy-to-visualize text. The page layout and brief chapters make it appropriate to assign supplemental readings along with the chapter topics. Some areas for improvement: use hyperlinks to reference forward and backward within the text so that readers can pop back and forth to related concepts. Include links in the text to reputable online materials or publications. See my comment below in Organization feedback concerning chapter ordering.

One thing that strikes me as amazing and also challenging about this text is the concision and simplicity for which Bhattacherjee integrates complex information. The chapters are very brief- about half of what would be a typical, field-specific textbook, but the content is simultaneously dense and clear. For example, Chapter 7 addresses scale reliability and validity. In just a few short pages, we get an incredible density of information and terminology, from a formula and brief explanation of Chronbach's alpha to exploratory factor analysis as a method to demonstrate convergent and discriminant validity. There is an appropriate number of tables to visually demonstrate complex topics in-text. Overall, the chapters are well-organized and easy to follow with a working knowledge of basic stats. The introductory chapters have been intentionally placed to introduce readers to basic principles. The following chapters could be assigned as readings in any order that fit with the student's needs (but I find the order of these chapters appropriate, as-is): Chapter 9 Survey Research, Chapter 10 Experimental Research, Chapter 11 Case Research, Chapter 12 Interpretive Research, Chapter 13 Qualitative Analysis, Chapter 14 Quantitative Descriptive Statistics, Chapter 15 Quantitative Inferential Statistics. The final chapter, 16, covers Research Ethics, which seems to have been lopped on at the end of the text. It would be a better fit in the first third; perhaps integrated into one of the first several chapters with a nod toward the evolution of social research.

Regarding navigation, the pdf online version does not allow for creative navigation through the document. Graphics and charts are clear and easy to see in the online pdf version. They are a little smaller than I would like on the page, but the text is clear and the tables and graphs are visually appealing. It looks like most of the graphics were created using PowerPoint. One odd thing I noticed is that the paragraph spacing is inconsistent. In one section, the spacing between paragraph lines seems to be set at 1.25, and then, for no apparent reason, the line spacing moves back to single space. This is not visually distracting, just peculiar. Overall, the graphics in the online version are much clearer than in the softcover print version, which prints only in greyscale, with quite a bit of granulated distortion in the figures.

I did not notice any writing errors.

The research topic examples represented a diverse array of research topics, methods, fields, etc. The overview of science, scientific research, and social science was welcomed and unique to this text. Some areas for improvement would be to include historical scientific figures who are not all male, and link critical methodology in a clearer manner with specific critical and cultural examples of this form of research.

Reviewed by Lee Bidgood, Associate Professor, East Tennessee State University on 10/29/19

The text seems comprehensive, covers a wide range of research approaches, and parts of the research process. I will have to supplement with more of the area-specific writing that my students need, but this is easily added in the adapted version... read more

This text seems to follow the path of other texts that outline research design and methods, such as the Creswell book that I have used for several semesters. I do not detect bias in the text, or any significant errors.

I will discuss disciplinary relevance rather than chronological applicability (which other reviewers have already addressed thoroughly). The course for which I seek a textbook is meant to prepare students in a non-discipline-specific regional studies context, and for a range of methodologies and research design possibilities, mostly in the social sciences and humanities. This text is most relevant to the potential research programs of our students in discussions of the precursors to research design in Chapter 2 (“Thinking like a researcher”) and of the using and creating of theory in Chapter 4 (“Theories in Scientific Research”).

The authors’ prose is clear and easily comprehensible. Definitions are clear, and sufficient (jargon is explained). There could be more examples to clarify and assure comprehension of concepts, I plan to add these in my adaptation.

There is not an overt intra-chapter organization scheme that is consistent from chapter to chapter--each chapter differs in the sorts of content, that some sort of generic outline would feel forced, I think. The “feel” of the text, though, is consistent, and effectively conveys the content.

Because it uses footnote citations instead of endnotes / parenthetical citations, each page contains all of the references contained on it, which helps with modularity. The portions of the text that are less relevant to the course I teach (i.e. the more technical and statistical chapters, such as Chapters 6, 7, 8, 14, and 15 are easily omitted; I will be able to adapt portions of this text (i.e. the discussion of sampling in Chapter 8) without needing to provide all of the chapters. Some of the more technical vocabulary will require editing and explanation, but this seems manageable for me as an adapter.

The book is logically organized and the topics make sense in the order presented. I agree with another reviewer that the ethics portion seems like an appendix, rather than an essential and structural part of the book. As I adapt this text, I would address ethics at the beginning (as I do in my current teaching of research methods) and infuse the topic through other sections to address ethics-related concerns at all stages of research design and implementation. The author’s choice to use footnotes for references is not the one that seemed logical to me at first - it seems “elegant” to put all the references in a list at the rear of a book; now, reading through the whole text, however, I see some value to having the entirety of a citation at hand when reading through the main body of the text. Still, I miss the comprehensive list of works cited at the end of the book, which I would add to a text that I create, since an e-text is not limited by the economics of physically-printed books.

The text is workable as presented in the PDF document that I downloaded. Charts and other imagery are usable. There are no extra navigation features (a link to take a reader to the table of contents in a header or footer, etc.). I am left wondering if, in a PDF form, an OER textbook would be more useful with more navigation features, or if they might make the document buggy, cluttered, or otherwise affect use.

I did not detect any issues with grammar, usage, etc. in the text.

There is a lack of specific examples that might lend a sense of wide scope / global appeal to the textbook, and create an inclusive atmosphere for a reader/student. The author has stated that they hope to translate and widely distribute the text - perhaps, as is the case in the syllabus that the author provides, the hope is that in use for a course, additional readings will provide local knowledge and place-, culture-, and discipline-specific details and context.

This is a solid text that will provide a framework for adaptation in another disciplinary / area context.

Reviewed by Kevin Deitle, Adjunct Associate Professor, TRAILS on 10/6/19

I am pleased with the coverage in the text; it includes the history and foundations of research, as well as chapters on ethics and a sample syllabus. The structure and arrangement of the book differs from my own understandings of research and how I present it in class, but all the material covered in my class appears in the text, and it can be ordered to fit my syllabus. This text spends more time with statistics than I include in a research course, but again, that can be omitted or just used for reference. The book does not include either an index or a glossary, which is unfortunate for anyone who wants a paper version. Of course, most students seem to prefer an electronic text, so I assume they use a search function rather than an index.

I have not spotted any glaring errors, other than an occasional grammatical slip or a cumbersome edit. The author includes a few citations, usually following APA style, but employs footnotes instead of a reference section. The content mostly aligns with my own conceptions of research, although it does have a different arrangement from my presentation in class. This does not suggest that the content is wrong, only that I would likely rearrange it to suit my instructional sequence. I sense no bias in the presentation, including the historical or ethical portions, or sections that mention religion. I’m comfortable that I could rely on this book in class without worrying over slanted content or editorialization.

Research is something of a traditional topic, in the sense that changes or evolutions move at a comfortably slow pace. I expect there is very little of this text that is likely to become obsolete any time soon. The flip side is there is little in this book that is necessarily cutting-edge, but that is not the fault of the author at all. And in the unforeseeable situation where a new protocol or a new advance in either statistics or research warrants an update, I think the organization and the modular design will allow that to happen without major upheavals in the structure or arrangement of the text.

As mentioned elsewhere, the writing is comfortably academic without becoming dense or burdensome. I have seen introductions to research that were more casual and probably fit a beginner audience better than this would, but I daresay this is intended as a core text for a graduate-level class, and for that reason, can be expected to sound less approachable and more authoritative. The text employs features for fast visual reference, to include breaks in the text to allow for visual elements, and bolded text where key terms are introduced or defined. While this would probably not be a particularly exciting text for a self-study course, it will sit well with classes that need a reference text that takes the time to explain concepts with some authority.

Structurally the author has a style and sticks to it throughout the text. Visually this book is sparse, and it will require some effort on the part of the professor to make the content digestible in a classroom environment. However, that also suggests that the arrangement and format remain predictable from the first page to the last, without any surprises in presentation or discourse. Research has a tendency to step on its own toes when it comes to terminology, but this text follows those conventions for the most part, making it mostly congruent with other research texts I have seen. I think this book would complement other research texts without causing too many difficulties in terminology or arrangement.

The author suggests in the preface that the work was intended to be rearranged by sections, and I can appreciate how the chapters and structure support that statement. I do see this more as a foundational reference for a graduate-level course than a self-study text though, and it has the feel of a reference work to it. Text appears in large blocks, is illustrated sparsely, and has no callout texts or pull quotes. Key words are bolded but get no more embellishment, which again suggests a reference rather than an instructional work. I’m sure this material could be the groundwork for a more reader-friendly presentation, if someone wanted less of a reference and more of a textbook.

This might be the most appealing point of the text for me. As I mentioned earlier, I like the overall sequence that the author follows, but at the same time I can appreciate how the sections can be detached and still stand alone. The logic follows principles and theory through to fundamentals, then diverges to cover the details that fit more complex or esoteric versions of research. There is enough statistical explanation to avoid vague generalizations, but at points I expect it would overwhelm a beginner. I would prefer ethics was near the start of the text, rather than an epilogue; our course is arranged to require students to complete ethics training before they may pursue later assignments. But this is easily solved.

On the whole the text is satisfactory, the layout from page to page is acceptable, but there’s a minimum of graphic elements or visual components. Some of the statistical formulas or graphs are low-quality, or have suffered compression artifacts. Their appearance in the text is logical though, and the few tables or diagrams that do appear are in color, with arrows or labels to ease interpretation. The table of contents is primitive, and there is no way to navigate specific tables or diagrams except moving page by page in sequence. External sites are hyperlinked, and the table of contents has been designed for electronic use, but there are no cross-reference features. This gives the text the feel of a word processed document converted to a PDF format, intended to be printed. Overall, the core content is strong, as a printed book it is probably acceptable, but as an electronic textbook it lacks some contemporary features.

I have found very few grammatical errors or incomplete sentences, and none of those were so flagrant as to make the text unusable. If this had been submitted as an academic work it would likely earn some criticism for style or grammar (the author seems to follow APA style, but tends to footnote references simultaneously), but this never impedes the delivery. The text is readable at a collegiate level without becoming over-academic, or for that matter, casual.

The text manages to broach sensitive issues in a level and balanced format; in particular the ethics section manages to discuss some well-known failings in past research without becoming overly critical of the researcher or the participants. Arguably, research and its underlying processes are mostly mechanical (or at least standardized), meaning it is possible for individual researchers to violate cultural, ethnic, racial, or other boundaries, but the underlying science is generally unconcerned with those issues. In that sense, the book has very few opportunities to broach hot-button topics except when dealing with historical or ethical examples.

I appreciate this text as a starting point for a more accessible design, or as a background reference for a full course introducing social science research. I see it as a foundation text or an external source for students who seek a concise fallback for lessons, and with content that is compatible with other textbooks. In many ways it needs much more to compete with established textbooks or dedicated electronic learning tools, and in some places I would like more references for the material that is included. On the whole though, I would consider this as the core text for my next introductory research course.

Reviewed by Krystin Krause, Assistant Professor, Emory and Henry College on 4/10/19

This text covers the core elements of a social science research methods course at the undergraduate level. While the notes state it is intended for graduate coursework, I would have no problem teaching in my undergraduate courses. The concise chapters are undergraduate-friendly and will make a solid foundation with the addition of supplemental reading assignments that show examples of the concepts discussed in the textbook. There is no glossary or index, but keyword searching in the pdf copy is simple and effective.

The text seems to be an accurate reflection of social science research methods, particularly when considering causal inference and hypothesis testing. If your course is also covering descriptive inference, you would want to supplement the text with additional material.

Research methods is not a subject that changes quickly, and thus this text will not become obsolete quickly. The only things that may need updating over time are any links that lead to pages that no longer exist. Any other updates will be relatively easy and straightforward to implement.

The text is written in a style that is accessible for undergraduates. It follows the conventions of including relevant key words and phrases in bold and includes easy to follow definitions of terms. I anticipate that undergraduates will also appreciate how concise the text is.

The chapters are consistent in both terminology and framework. It offers a unified organization that also allows for mixing and matching chapters if an instructor wishes to teach the chapters out of order.

The organization of the text lends itself to be adapted to any introductory social science research methods course, regardless of what order the instructor wants to place the topics being discussed. Chapters could be taught out of order and can be subdivided accordingly.

While it is certainly possible to break apart to teach the text in a different order than how the chapters are originally offered, the progression of the text from the introduction to the chapters on qualitative data analysis is both logical and clear.

The text is free of interface issues, and charts and images appear to be clear and correct. The only exception to this are the links found in the sample syllabus at the end of the book. I was only able to get one of the links to work.

No grammatical errors jumped out at me. There are a few here and there, but they are not distracting for the reader.

The text is not culturally insensitive or offensive.

Because the book is concise, I would recommend its use in addition to other supplementary resources such as class lectures, academic articles that demonstrate the methods discussed in the textbook, and projects that allow students to experience the methods first-hand. It would make a good alternative to more elaborate basic research methods textbooks when the instructor wishes to keep costs for the students low.

Reviewed by Mari Sakiyama, Assistant Professor, Western Oregon University on 4/5/19

The textbook covers the major key elements that are essential in research methods for social science. However, both the breadth and depth of information might be too elementary for Ph.D. and graduate students. With the use of additional reading... read more

I did not notice any errors or unbiased content. The author had provided accurate information with simple/straightforward examples that can be understood by students with various discipline in social science.

Given the nature of the subject, the content is considered to be up-to-date. However, although there will not be too many changed expected in the research strategies and designs, it is important to note that some of the sampling procedure have been facing some changes in recent years (e.g., telephone survey, online sampling frame).

The textbook provided the content in a clear and concise manner. The author, instead of providing a complex list of academic jargon/technical terminologies, but rather clarified and explained these terms in a simple and straightforward fashion.

Overall, the content was consistent throughout the textbook. Starting with a broad/general statement of each chapter topic, the author narrowed it down to smaller element which is easy for the reader to follow and understand. As he provided in CH.6, it might be even more helpful to have summaries for each chapter.

This textbook is certainly divided into smaller segments, but maybe too small (short). However, as mentioned above, this problem can be solved by adapting additional readings.

The textbook is significantly reader-friendly and well-structured. Although some instructors prefer to cover some chapters earlier (or later) in their semester/term than others, this is just a personal preference. There are no issues with the author’s organization of the textbook.

Overall, the use of indentations, bolding, italicization, and bullet points, was consistent. However, many of the images were blurry (e.g., Figure 8.2, Table 14.1) and some fonts were smaller than others (i.e., pg. 34).

I did not notice any grammatical errors. Even I had missed some, they would not be destructions for the reader. (Note: The scale is confusing. What I mean by '5' is the least amount of grammatical errors were found)

The author did not use any concept that was insensitive or offended people and/or subjects from various backgrounds. (Note: The scale is confusing. What I mean by '5' is the least amount of cultural insensitivity or offensiveness were found)

See my comments above.

Reviewed by Candace Bright, Assistant Professor, East Tennessee State University on 11/7/18

There are some key elements that I would expect to be in a social science research methods book that are missing in this book. I think this comprehensiveness may be appropriate for an undergraduate course (with some supplementation), but the text... read more

The information in the book seems accurate. When necessary, it is cited appropriately.

The content is very relevant. Because the book focuses on methods, it does not need too much change over time. It was published in 2012. The main area that might need to be updated in the discussion regarding the Internet and how it impacts our research options. Perhaps more could be added on machine learning, AI, web-scraping, and social media in general. I increasingly see studies conducted either using social media content or recruiting through social media; neither of these are addressed in this book.

I really like the way the book is laid out. In particular, the qualitative and quantitative analysis sections are well organized. They succinctly cover a lot of information is a way that is very consumable. There were some instances, however, where I thought wording lacked clarity or definitions needed further explanation.

I do not see any issues with consistency.

I like the organization of this book and each chapter does a good job of standing alone on important topics within research methods. The sections within the chapters are clearly marked and logically organized.

The organization is clear and logical. It covers important concepts in research methods in the same order in which they are typically taught, with the exception of ethics. In this book, ethics comes last, whereas I would have taught it earlier.

This might be minor, but I noticed some places where the spacing was different and it was a little distracting. Overall, it is well formatted.

I didn't notice any grammatical errors.

Overall, the text book could use more examples and applied examples, but when present, I find them culturally appropriate.

I have mixed feeling on the image on the cover and the limited visuals within the book. I also don't feel like this textbook has enough visuals or figures that could be used to support comprehension of the materials. More examples would also be helpful. Overall, however, the author has presented a lot of information succinctly and I look forward to using this text (in parts) in future methods courses.

Reviewed by Alysia Roehrig, Associate Professor , Florida State University on 11/5/18

This text provides an overview of many important issues for my graduate research methods course in education. There are a few important topics missing, however. In particular, types of correlational designs and mixed-methods designs would be important to include. Likewise, single-subject designs are not mentioned at all. I will have to supplement these areas with other readings. I also think more about specific threats to internal and external validity should be provided, along with information about when and how certain threats are avoided. There is no glossary but being an online text, it is simple enough to search for certain terms.

Content seems to be error-free and unbiased for the most part. However, I have an issues with the language in chapter 2 about about strong and weak hypotheses because it seems to treat the experimental/causal hypotheses preferentially. The author also states that hypotheses should have IVs and DVs...but what about non-experimental hypotheses?? I think students could be misled by this and I think this requires a lot of unpacking. Thus, I do sense somewhat of a prejudicial treatment of quantitative and experimental research methods. I plan to add information to pages 13 and 15 about how qualitative methods do not involve testing hypotheses though the results might be an inductively derived hypothesis or nascent theory.

The content covered is pretty standard and basic and so not likely to be out-dated soon.

The writing is straightforward and easy to follow.

The use of terms and framework seems to be consistent throughout the book.

The chapter and subject headers all seem to be clear. They will make it easy to select sections for assignment or reordering if revising for use.

The order of topics makes sense and is aligned with the process of conducting research.

The hotlinks in the table of content are nice, but additional navigational aids would be helpful. For example, a back to the Table of Contents (TOC) button would be nice, as well we a list of all subsections (hotlinked) added to a long version of the TOC.

I have not noticed any egregious problems.

There are not many examples, which means there is little opportunity to offend.

Reviewed by Eddie T. C. Lam, Associate Professor/Editor-in-Chief, Cleveland State University on 9/12/18

The book provides ample information for a research course, but it may not meet the needs of every instructor. For this reason, the book should include a few more chapters so that course instructors can have more options for a semester-long research course. For instance, at least one chapter should be on nonparametric statistics and their applications on research studies, while another chapter should be on research paper writing (e.g., what should be included in the Introduction, Methods, Results, Discussion, and so on). For the Appendix, it is nice to provide a sample syllabus for the instructors, but the students may want a sample research paper in proper journal or thesis/dissertation format.

Most of the information presented in this book is accurate. The author has mentioned in Chapter 5 (p. 37) that “construct validity” will be described in the next chapter, but I don’t see any construct validity in Chapter 6 or Chapter 7. In addition, the author may want to emphasize what “alpha is set to 0.05” means. Does it mean the p-value has to be less than 0.05 (p. 125) or p ≤ 0.05 (p. 130) to reject the null hypothesis?

In terms of content, the book has fairly good amount of information. However, it is also obvious that many terms appeared in the last few decades are missing from the book. For example, Survey Monkey and social media can be included in Chapter 9 (Survey Research) and structure equation modeling can be introduced in Chapter 15.

The information is presented in layman’s terms without any jargon. New terms are bolded with clear definition, and sometimes they are illustrated with examples.

The terminology and framework are consistent throughout the text.

The chapters are logically presented and they are grouped under different sections. As mentioned before, the text should add a few more chapters for the course instructors to select from.

In my opinion, “Chapter 16 Research Ethics” should not be standalone (under the “Epilogue”) and it could be part of the “Introduction to Research” (i.e., the first few chapters).

The text does not have any significant interface issues, though the font size of the figures can be larger (e.g., they should not smaller than the font size of the text).

Overall, the text contains very few grammatical errors. However, in a number of occasions, a comma is added for no reason, such as “. . . we must understand that sometimes, these constructs are not real . . .” (p. 44). It is also unnecessary to always add a comma before the word “because.”

The content of the text is not culturally insensitive, and the author does not present any offensive statements or comments anywhere in the text.

It’s time to have a second edition.

Reviewed by Amy Thompson, Associate Professor, University of South Florida on 6/19/18

This text is a nice overview of some of the key points in social science research. There are useful definitions of key terms throughout the book, although none of the chapters go into much depth. It should be noted that there is more of a focus on... read more

Overall, the text seems accurate. There are some cases when the author gives advice that I don't agree with (i.e. advises against even-numbered Likert scale items, p. 48; encourages people not to do "trendy" research, such as that on new technology, p. 24). Even so, most of the information seems to be accurate.

The book is relevant. It gives a good overview of the theories and methods, which change little over time. I would suggest a few updates, however. Currently, there is controversy on the over-reliance of the p-value, and it would be useful to include some of this discussion on p. 125. Also, on p. 73, the author talks about "mail-in" and "telephone" surveys as a research method, and even goes on to say on p. 74 that most survey research is done by self-administered mail-in surveys with a pre-paid return envelop. This information needs to be updated, as currently, much of the survey research is done via online platforms.

The book is quite clear and provides succinct definitions.

The book seems consistent throughout.

The chapters are short and very readable. There would be no problem dividing the chapters up for a class, or using a portion of the book.

The topics are presented in a logical manner.

The text in some of the tables is blurry, especially when enlarging the PDF. Perhaps the print copy is clearer. The text outside of the tables is clear.

I didn't have any trouble reading or understanding the text.

This book is not offensive.

Overall, this is a good book to have as a reference or an additional text for a class. For my field, it wouldn't be sufficient to use as a stand-alone text. Although its intended audience is graduate students, it's a bit too basic for Ph.D. students, in my opinion. It would be a good text for an intro to research class at the UG or MA level, as a supplemental text. I would recommend it to Ph.D. students to use as a reference because of the key terms included. It's great that a resource like this is available for free to students and faculty in a wide variety of disciplines.

Reviewed by Huili Hao, Assistant Professor, University of North Carolina Wilmington on 5/21/18

This book provides an introductory and broad review of some of the key topics in social science research including research theories, research design, data collection, data analysis and research ethics Students from different disciplines in social science will find these topics useful in developing their research method skills. However, the book falls short on the depth of the essential concepts. It would also benefit from offering more practical examples for some of the theories or terminology. A glossary is not found within the text, although the table of content lists the topics covered in each of the modules.

Overall, this textbooks seems to be accurate.

The relevancy and longevity of this book are great. It focuses on fundamental research methods as well as incorporates current research approaches. Given the nature of research method that does not change drastically, content is up-to-date and won’t make the text obsolete within a short period of time. The topics are written in the way that necessary updates will be relatively easy and straightforward to implement.

The text is written in a logical and concise fashion. The text is easy to follow. I did not find any jargon or technical terminology used without explanation.

The text consistently matches the topics outlined in the table of content.

The text is clearly organized into five modules: introduction to research, basics of empirical research, data collection, data analysis, and research ethics. It also includes a course syllabus, which is nice and useful. Each of the modules / chapters can also be used as subunits of a research method course without putting the reader at a disadvantage.

The table of content is clear and the chapters are organized in a logic order.

I downloaded the PDF version of the textbook and find it easy to read offline. The formatting, navigation and images/charts seems clear and appropriate.

I had no trouble reading or understanding the textbook.

Overall, this is a good textbook that covers a broad range of topics important in research method. As this textbook is designed as a succinct overview of research design and process, more practical topics are not included in much detail such as how to conduct different statistical analyses using SPSS or SAS, or how to interpret statistical analysis results. It would require additional materials / textbooks for graduate level research method courses.

Reviewed by Jenna Wintemberg, Assistant Teaching Professor, University of Missouri on 5/21/18

I use almost the entire text in an undergraduate Health Science research methods course. I do supplement the text with additional readings on: -selecting a research topic -developing a research question -how to read scholarly articles -how to search the literature -mixed methods research -community-based participatory research -disseminating research findings -evidence-based practice

I have found this text to be accurate, error-free and unbiased.

The content is written in a way that will allow for longevity of use. I compliment this text with current peer-reviewed journal articles which are relevant to my students' career paths and can be updated more regularly.

I have found the book to be clearly written and appropriate for upper-level Health Science undergraduate students. Technical terminology is sufficiently defined.

The text uses a consistent framework throughout.

The text is easily divisible into smaller reading sections. I assign the chapters in an alternative order and students have not had problems with this.

I assign the chapters in an alternative order for my undergraduate students. For example, I have students read chapter 1 following by chapter 16 (research ethics).

There are no interface issues.

The text is free of grammatical errors

The text is not culturally offensive.

Because of the basic nature of the materials presented and clear writing, my upper level undergraduate students have done well with this text. The brevity of the chapters and bolded key terms particularly appeal to the students. I do have to supplement the text with journal articles and other materials. However, I am pleased with this straight-forward text and will continue to use it as the main text in my course moving forward.

Reviewed by Amy Thompson , Associate Professor, University of South Florida on 3/27/18

Reviewed by Debra Mowery, Assistant Professor, University of South Florida on 3/27/18

The text covers all of the areas of basic research information that I cover when I teach research and research methods in the social sciences. The table of contents is straight forward, and the chapters are arranged in a fluid, logical order. The nice thing with this text is that you could rearrange as you see fit for your course without an issue. There is also a sample syllabus in the appendix which could be useful when setting up a course. I feel this text is great for students who may not necessarily be interested in research as a job prospect (their interests may be more clinical in nature) but need the basics of research in a clear, easy to understand, and straight forward format.

I felt the content of this text is accurate, unbiased, and free of any glaring errors..

This text appears to be up-to-date including issues such as web-based or internet surveys and questionnaires. I did see that the copyright for this text was 2012 so not sure if revisions or updates to the original have happened or not. It seems that there should be a way to document if this is the latest version of the text. This may be useful information for users of this text.

This textbook is written in a concise and easy to read and understand manner - it is very user-friendly. This is a plus for students - it means they may actually read the text! Jargon and acronyms were appropriately defined with an explanation of how the terms originated and came to be utilized in research. This is appealing to me as an instructor so there is background information for the students.

The consistency of this text is uniform throughout. One appealing issue I liked was the use of social science examples when explaining topics like theories or paradigms. In some research texts examples are utilized but they may not necessarily be in the discipline that you are teaching.

I do like that this text is divided into 16 chapters which is perfect for a 15/16 week semester. The chapters are not so overwhelming that other supporting readings cannot be assigned to students as well to assist with explanation of the weekly topic. The text serves as a great base for building weekly assignments/readings for students.

The majority of the text is presented in a logical format. One issue I had with the order of the chapters in the text was including Ethics at the end in the Epilogue as if it was an after thought. Ethics, ethical behavior, and rigor are a must in research and should be addressed early on in the research process. Having said this, I feel the chapter on Ethics should be moved up further in the chapter line-up (possibly to chapter 2 or 3).

I did not experience any navigation problems. There was however, distortion with many of the images especially the graphics that were utilized throughout the text. A review of the images/graphics and an update to them would be useful. If this e-text has not been updated since 2012 this may be the issue for the distorted figures.

There are a few grammar/spelling/word choice errors. The errors do not effect the content of the text but when reading it makes you pause and think - what is trying to be said here? It might be useful to the author to have the text proofread or copy edited to resolve these issues.

In reviewing this text I did not see any examples that might be deemed offensive or insensitive to other cultures, orientations, ethnicities, etc,

Reviewed by Kendall Bustad, Clinical Assistant Professor, University of Maryland, College Park on 2/1/18

This book covers all the important topics in social science research and is approachable regardless of discipline and course level (high school, undergraduate, graduate, and even post-graduate). It provides an introduction to philosophy as well as components of research. You'll find yourself returning to the basics, and it gives strong foundations. Specifically, I find that the book provides a very comprehensive introduction to research philosophy and research designs, particularly in addressing how to come up with research questions, which is often a challenge for new doctoral students. However, due to the succinct nature of the book, some sections seemed lacking. Particularly, in the more practical steps of the research process (the data collection and data analysis sections)

The text does not seem to be biased in any way.

The content of the book is up-to-date. The text included relevant descriptions of current software commonly used in research.

If you want to have a compressed body of knowledge of social science research, you may read this one. Beneficial.

The text consistently matches the book outline. Terms were used consistently throughout the text.

Each chapter can stand along as a separate lecture. The headings, subheadings, an bold items are great additions that highlight important topics or definitions.

Most of the text flows in a logical, clear fashion. However, it may be clearer to have quantitative data analysis methods immediately follow quantitative data collection methods, and similarly for the qualitative data collection and analysis.

No issues noted.

There are a few grammatical errors.

There does not seem to be any culturally insensitive or offensive text.

Reviewed by Jason Giersch, Assistant Professor, UNC Charlotte on 2/1/18

The biggest challenge faced when writing a book about research methods is the decision about what NOT to include. Instructors and disciplines within the social sciences vary widely in terms of their expectations of students in an introductory methods course, and thus their needs from a textbook also vary. This textbook does an excellent job setting the stage for what we mean by "research" in the social sciences. Students will develop a solid foundation in the goals and rationales behind the methods social scientists employ. Students will also develop a comprehensive vocabulary in social science research methods. However, the book falls short in the development of students' research skills. Learning about methods is important, but not much is gained from that knowledge unless the student also learns how to execute at least some techniques. Furthermore, there is little guidance for the student regarding how to properly write a research paper, something that many instructors will find disappointing. This book is probably comprehensive enough for a 3-credit methods course with test-based assessments in a program where few students pursue graduate work. But if teaching students to actually conduct and write up research is important to the course, there are much better books out there (although at significant cost).

Content is accurate and unbiased.

The relevance and longevity are strong. This book describes some of the most current methods but still focuses on the foundations of research that will be appropriate for the foreseeable future. Updates could be easily made every five years or so to keep up with methodology.

The writing is very easy to follow with helpful examples. Prose is direct and to the point, giving only the essential information so as to allow the learner to develop a grasp of fundamentals. The section on theory, for example, is refreshingly clear for learners. Graphics aid in understanding the material in many parts.

This textbook uses consistent terminology and framework.

The textbook is appropriately structured for a standard 15 week course and even recommends a syllabus. Adapting it to other formats, like a 5 or 10 week summer course, might be tricky. There are ample headings and sub-headings, however, that allow the text to be divided into smaller chunks, which is nice to see given how many students feel overwhelmed by this topic.

Organization and flow is excellent. From an education and instructional standpoint, I wouldn't change the organization.

The simplicity of design is a strength -- students should have no difficulty opening and viewing the text on a wide variety of devices. On the downside, there are no bells and whistles that many some students have come to expect from online textbooks.

The casual writing style makes it very accessible, but one consequence is the very occasional grammar problem. It's a trade-off, I think, that is worth making.

Research methods are pretty "culturally-neutral", so there's nothing in it I would see as insensitive or offensive. That being said, the text recommends SPSS and SAS as software to use while neglecting free options (like R) or more ubiquitous programs (like Excel). For a textbook intended to keep costs at zero, these are glaring omissions.

I could certainly see this book being used as an accessible and low-stress introduction to the world of research methods in the social sciences. The main improvements I would like to see would be (1) sidebars throughout that guide students through the paper-writing process and (2) activities using datasets for students to actually perform some of their own quantitative analyses. Perhaps a companion volume could address these needs.

Reviewed by Nathan Favero, Assistant Professor, American University on 2/1/18

This text provides a fairly comprehensive coverage of topics. It is broad, hitting most of the major topics I need to cover in an intro PhD seminar for social science research methods (I'm teaching public administration/policy, political science, and criminology students). That said, there is not a ton of depth in this textbook. I don't view that as a negative; I prefer having a textbook that gives a basic outline of essential concepts and then fleshing this out with supplemental readings, but some might prefer a textbook that goes into more depth.

Overall, this textbook is accurate but not perfect. Sometimes I wish it was a bit more precise, particularly in coverage of quantitative topics. But I use another textbook to more fully cover quantitative topics anyway for my course.

I would say this textbook reads as modern and relevant, although perhaps it could do more to address emerging methodological concerns in social science disciplines (p-hacking, replication, pre-registration of research designs, etc.).

The textbooks is very accessible and easy to read for someone new to the disciplines of social science.

The book appears to be consistent.

I've assigned students to read the chapters in a different order than they are presented in the text had have not encountered any problems. Chapters are coherently organized into distinct topics.

The organization of the book is logical.

Overall, this book is easy to read and use. Graphs are not always high-resolution, but they are readable.

I have not noticed many grammatical errors.

I have not noticed any clear biases or insensitive handling of material in the book.

I'm delighted to have found this book. It's a great starting point for teaching my students to think about the basics of social science research and provides a nice skeleton on which I can layer more in-depth material for my course.

Reviewed by Holly Gould, Associate Professor, Lynchburg College on 8/15/17

The author states that the text is not designed to go in-depth into the subject matter but rather give a basic understanding of the material. I believe the author covers the necessary topics with enough depth to give the reader a basic... read more

I found no errors in content and no observable bias in any of the chapters.

This text will continue to be relevant because of the nature of the subject matter. Updates may be needed to reflect more current research or trends, but no major changes should be necessary.

The text is written clearly and succinctly. The text is understandable for those who are new to the subject matter.

I found no inconsistencies in the text.

The text is divided into logical chapters, and subheadings seem to be appropriate. Chapters can be read fairly easily in isolation without putting the reader at a disadvantage.

The topics are presented in a logical fashion. Some of the chapters have summaries or conclusions, while other chapters seem to end abruptly. It would be helpful to the reader to have a summary statement at the end of each chapter.

I downloaded and read the text in a PDF reader and had no trouble with formatting, navigation, or images/charts.

The text contains some grammatical errors but the errors are minor and do not distract the reader.

This text is well written and I would recommend it to an individual looking for a bare bones book on basic research methods. It contains information essential to understanding quantitative and qualitative research. The charts and images provided enhance the understanding of the text. At times, the author digs a little deeper into background and formulas for certain statistical ideas, which may be unnecessary to someone looking to understand the basics (e.g. the formula for Cronbach's alpha). Some chapters seem to end abruptly while other chapters have excellent summaries or conclusions. There is one recommendation that goes against the prevailing wisdom on survey design. On page 77, the author indicates that a survey should begin with non-threatening questions such as demographic information. Many experts have written that these types of questions, when asked at the beginning of a questionnaire or survey, can affect the respondents' answers to subsequent questions and should be saved for the end. Aside from these minor issues, this text is a great resource and I recommend it.

Reviewed by Virginia Chu, Assistant Professor, Virginia Commonwealth University on 4/11/17

The text offers an introductory overview to scientific research for PhD and graduate students in social sciences. It covers a broad range of topics, research theories, research process, research design, data collection methods, qualitative and quantitative research, statistical analysis, and research ethics. This book touches on many important topics related to the scientific research process that is typically found in several different text. As the author stated in the preface, this is an introductory book that is minimalist by design, it does not contain in-depth discussions or many examples. This is both a plus and a minus, as it makes the book more compact and allow it to be used by many different disciplines, but may be harder for students to relate. The comprehensive nature of the book allows the reader to be exposed to all the necessary topics, or provides a structure for a course instructor, who then supplements with additional materials to create the depth that is specifically tailored for their discipline. Specifically, I find that the book provides a very comprehensive introduction to research philosophy and research designs, particularly in addressing how to come up with research questions, which is often a challenge for new doctoral students. However, due to the succinct nature of the book, some sections seemed lacking. Particularly, in the more practical steps of the research process (the data collection and data analysis sections), as a new doctoral student will certainly need more details than what is provided in the text to begin their first research endeavor. For example, in the quantitative analysis section, only a handful of basic analysis were discussed in detail (univariate analysis, hypothesis testing, t-test, regression). I would like to see a more practical discussion of ANOVA, as it is a very commonly used statistical analysis tool. These topics may also be more discipline specific, where instructors of research classes can supplement with additional materials. The discussion on research ethics is certainly a nice addition to the book where many other research methods texts lack. An index/glossary is not included with the text, but the table of content clearly outlines the topics discussed for each module.

The book is overall accurate and unbiased. The book covered different social science research methods fairly. I did notice a discrepancy in Figure 5.1, where “single case study” is plotted on the graph as high in external validity, but the rest of the text frequently brought up case studies (especially single case studies) having the difficulty with generalizability which should have low external validity.

The content of the book is up-to-date. The text included relevant descriptions of current softwares commonly used in research. It will also stand against the test of time as research methods do not change drastically. The content can also be updated to reflect new technological updates. One needed update noticed is on page 120, where the authors cautioned that only smaller datasets can be stored in Excel and larger datasets needs a more elaborate database system. While the statement is still relevant, the numbers the author cited appear to be old and Excel has since been updated to handle larger datasets (1,000,000 observations and 16,000 items) than what the author had listed.

The content is written in a very clear and concise manner. It is easy to read and to follow the author’s arguments. I did not notice any jargon or technical term that was used without explanation.

The book has a modular organization, with each chapter designed to be used for a different lecture. Each chapter is a self contained unit that can be used as its own reading. Each chapter also has subsections that are clearly marked with subheadings. Important terms are also highlighted by bolding, making it easy for the reader to identify the important concepts.

The chapters of the book flows logically from one to the next. The current layout of the text groups all the data collection methods together and all the data analysis methods together. It may be clearer to have quantitative data analysis methods immediately follow quantitative data collection methods, and similarly for the qualitative data collection and analysis. This could be easily done based on the course instructor preference.

No interface issues noted.

The text is generally free of grammatical and spelling errors, with the exception of 2 minor typos noticed on page 139 (“Rik”, “riska”).

The text and examples provided are not culturally insensitive or offensive.

The text is easy to read and covers a broad and comprehensive range of topics important for research. I particularly enjoyed the discussion on research ethics which is often missing in many research methods texts. I would recommend discussing that topic earlier, together with research design, as many of these ethical issues and IRB requirements come up during research design phase. As the text is a meant to be a concise overview of the research process, the more practical topics are not covered in as much detail and would require supplementary material.

Reviewed by Brock Rozich, Instructor, University of Texas at Arlington on 4/11/17

The textbook covers the majority of what would be expected for a research methods course. It builds upon basic topics to more advanced concepts, so students from various backgrounds of research experience should still find the text useful. The glossary for the text is clear and a sample syllabus is provided by the author for individuals wishing to use this text for their course. The text was lacking an index, which would prove helpful for students.

The text is accurate and up-to-date with research methods in the social sciences. A variety of data collection methods and concepts are discussed in an easy to understand manor.

The content is up-to-date with research methods in the social sciences. The text should be able to prove useful for a research methods or as supplementary material for a statistics course for the foreseeable future. While I looked through this text with a focus on using it for a psychology course, I feel that this text would be useful across other fields as well.

The book was clear and built upon concepts in a thorough manner. Technical terms were well defined, though as mentioned previously, an index would be helpful for this text for students to look up key terms if they became lost. The text would be useful for an upper-level undergraduate or introductory graduate level course.

The text is consistent throughout. There were no notable deficiencies in any of the content provided in each chapter.

The course is broken down into logical subsections and chapters. Introductory topics relating to research methods are provided early and are built upon in subsequent chapters. A sample syllabus and course outline are provided for instructors who wish to utilize the text for their class.

The book is constructed in a well-organized fashion, without any issues of chapter structure.

The PDF version of the text worked wonderfully on a laptop, with no issues of navigation or distortion of images. This text was not, however, viewed on a tablet or e-reader, which many students use for classes. Based solely on use of a PDF file on a laptop, the interface was flawless, however, if you are considering using this for a class, I would test it out on an e-reader/tablet first to make sure there are no issues with format/text size, etc.

The book did not appear to have any noticeable grammar or syntactical errors.

There were no notable instances of cultural insensitivity throughout the text. Examples were broad and not specific to an individual race or culture.

This is a wonderful open source option for a main text for a research methods course or as a supplementary option for a statistics course that also focuses on data collection.

Reviewed by Divya Varier, Assistant Professor, Virginia Commonwealth University on 2/8/17

The textbook adequately covers most fundamental concepts related to research methods in the social sciences. Areas that would need attention: a chapter introducing mixed methods research, and a deeper discussion on Research Ethics. More social science based examples on specific research designs, experimental research would be great. The research process could include steps involved in academic research with information on the publishing and peer review process.

Content is accurate for the most part. I would have liked a more nuanced discussion of reliability and validity concepts- introducing the concept of validity as conceptualized by Messick/Kane is needed. In social science, especially education (the field I work in), masters/ doctoral students need to be introduced to the complex nature of establishing reliability and validity. While the content covered is detailed, a more critical introduction of the concepts as being situated in the obtained scores as opposed to the instrument itself would have made the chapter stronger.

Content is for the most part up to date (see above comments for specific areas: reliability, validity, mixed methods); some examples may become outdated very soon (example of political movements in middle eastern countries for example).

The writing is excellent in terms of clarity. I appreciate the use of straight forward language to explain the multitude of concepts!

The text is consistent in its overall approach to research methods as well as consistent in its use of terminology.

Bold font for key terms is appreciated. More insets/boxes within chapters would be a great addition visually. Addition of research studies and discussion questions would be great.

The chapters are well-organized. Only suggestion would be to introduce research ethics early on in the book.

No issues whatsoever in this regard.

No issues with grammar

The text is best suited for universities in western countries although I did not identify any insensitivity that would hinder teaching and learning of research methods using this textbook elsewhere.

Specific chapters in this book will be useful for me, from an instructor's perspective. For example, Chapter 2 - 'thinking like a researcher' is wonderfully written. The chapter on Interpretive Research and Qual. Data Analysis are thorough and clear in presentation of concepts- I definitely would use these chapters in my Research Methods class.

Reviewed by Rachel Lucas-Thompson, Assistant Professor, Colorado State University on 12/5/16

As acknowledged by the author in the preface, this is intended as a survey book that doesn't cover all topics in great detail. The upside is that this is a flexible text that can be used in many disciplines; the down side is that the text is short on examples, which reduces readability. I also prefer a textbook that provides a more detailed discussion of the following issues, but could supplement the textbook with these discussion in class: a) confounding variables, b) writing a research report, and the parts of a research report, c) evaluating the internal and external validity of a study, d) how we handle Likert and Likert-type scales (with better reflection of the rich controversy about this issue), e) historical background that has informed our current ethical guidelines, and f) more detail about manipulated vs. observed independent variables. Also, the 'research process' section doesn't include a step for going through IRB review and approval, so overlooks an important step in social science research. I think more detail is provided about paradigms and theories than is necessary, but those chapters and sections could be left out of course reading assignments quite easily.

In general, I think this textbook would be best suited to a course where the textbook is seen as an overview to supplement course discussions rather than a detailed coverage of research methods principles.

As far as I can tell, the book is accurate. There are some terms that the author uses that are not widely used in my field (developmental psychology, human development & family studies) but the descriptions are clear enough that I think students will be able to understand what is meant (however, it would be great to acknowledge and discuss some of these variations in terminology so the burden isn't entirely on the students who are still learning these concepts).

Research methods and statistics content are unlikely to change rapidly, although with the increasing use of ecological momentary assessments, daily diaries, and internet sampling techniques, it might be useful down the road to include more detail about those techniques.

The book is easy to read and follow, although the lack of examples to clarify concepts sometimes reduces the clarity of ideas (but is in keeping with the philosophy of the book).

I haven't spotted any problems with internal consistency.

It would be very easy to divide this into smaller reading sections and assign at different time points.

In general the organization makes sense; the only exception is having research ethics as an epilogue, when ethical issues need to be considered before a study is completed.

My two suggestions for increasing are a) hyperlinking the table of contents so that it was easier to find exactly what you want in the textbook, and b) providing a more detailed table of contents (with subheadings) so it's easier to determine where in chapters you should reference.

I haven't found any grammatical errors.

The text is neither culturally insensitive nor offensive.

I think this book is very well-suited for intro graduate level courses in research methods, as long as instructors are comfortable with this as an overview supplement rather than a detailed stand alone resource for students.

Reviewed by Robin Bartlett, Professor, University of North Carolina at Greensboro on 12/5/16

Generally the major topics are covered. The table of contents (chapter listing) makes it easy to find content. Occasionally I found what I thought was a topic covered only minimally in a chapter - but then found additional information in a later chapter (e.g., treats to internal validity). Overall I'd say in comparison to most other texts with which I am familiar that most all topics are covered, to some degree, but some topics are covered less than I would expect in a doctoral level textbook.

I found no errors in fact in the textbook. I found it to be written in an accurate and unbiased manner.

Primarily due to the topic covered (research methods), I do not believe the text will become obsolete in a short period of time. I think updates could be easily added, and if the author decided to cover some topics more thoroughly, that could be accomplished relatively easily, too.

The book is written in an easy to read style. It is easy to understand. Technical terminology is explained appropriately. The author puts many words in bold type and then defines or describes the word. Students will like this approach.

I had no issues as I reviewed the book in terms of consistency of terms used. The text is internally consistent.

The chapters of the book are separated by natural divisions. It would be easy to use this book in a course on research methods, in fact, there is a syllabus included at the end of the book that could be used by a faculty member when course creating.

The textbook topics are presented in a logical fashion. The ordering isn't necessarily the same order I have seen in other texts, but the order is reasonable.

I had no major interface problems as I reviewed the book. Some of the diagrams in the book are a little out of focus, but, they are still readable.

I found no grammatical errors in the sections of the book that I read.

I found no cultural insensitivity in the text. I noticed the examples cited were from articles written by authors from different countries.

The book is easy to read and fairly comprehensive in terms of topics covered. Some topics are covered in less detail than in some other books I've had the chance to read / review. I am most accustomed to finding discussion of theories in separate texts and presentation of statistics that might be used to analyze quantitative data in separate texts. There are even a couple of chapters on qualitative methods in this book. So, the book covers a wide variety of topics and introduces them in a clear way. Topics are not covered in as comprehensive way as in many texts.

Reviewed by Kelly Pereira, Assistant Professor, The University of North Carolina at Greensboro on 12/5/16

This text offers a comprehensive overview of social science research methods appropriate for advanced undergraduate and graduate students. The text covers the basic concepts in theory, research design and analysis that one would expect of a text geared toward the social sciences in general. The text could be easily adapted and/or supplemented to fit any discipline-specific needs. While the text covers a broad array of topics, it is a bit superficial and lacks depth in some areas. More examples and case studies, for example, could improve the text's thoroughness. The text also lacks an index, glossary and discussion questions, all of which would have been quite useful for a text of this nature. I do like that it includes a chapter on research ethics and an appendix with a sample syllabus, however.

Based on my review, the text's content is accurate, error-free and unbiased. I liked that it presented both qualitative and quantitative research methods fairly, as this divide is often a source of bias.

The text contains up-to-date approaches to research methods and presents classic theoretical debates. The methods presented should not become obsolete in the near future. Any new trends in research methodology could be easily updated in future versions of this text. I feel the text will be relevant and useful for multiple years.

The text is generally well written. It presents the information in a clear and concise way. I find it provides sufficient contextualization and examples for graduate students with some background already in research methods. Undergraduates will likely require supplemental materials and additional case studies to grasp some of the concepts covered. The illustrations do help guide understanding of concepts presented.

The terminology and research methods frameworks presented in the text are consistent. The use of bolded terms and illustrations throughout the text provide additional consistency.

The division of the text into the following sections: theoretical foundations, concepts in research design, data collection and data analysis, make it easy for instructors to structure a course and assign readings based on these main foundational areas. This format also enables instructors to easily supplement with other materials.

Overall, this is a well-organized text. Bolded words/phrases throughout the text provide some structure to guide reading. The text is divided into 16 chapters, which corresponds seamlessly with a 16-week semester. This enables instructors to cover one chapter per week, if they so desire, or optionally spend more time on chapters relevant to their course and exclude others. As mentioned earlier, the logical division of the text chapters into the areas of theory, research design, data collection and data analysis, lends to a soundly-structured course and facilitates the assignment of readings and other coursework.

I did not experience any issues with the text's interface, navigation or displays of images/illustrations. The text is in PDF format.

I did not notice any grammatical errors that impeded reading of the text.

I did not come across any culturally-insensitive or offensive passages in the text.

Reviewed by Peter Harris, Assistant Professor, Colorado State University on 12/5/16

This is a comprehensive overview of research design and research methods in the social sciences. The book's introductory sections offer a discussion of the philosophy of science, the history of science, and definitions of some key terms and concepts, which will help students to contextualize their own endeavors - and their own discipline(s) - inside a larger framework. It also tackles the more familiar topics of research design - conceptualization, measurement, sampling, and so forth - and several specific approaches to data-collection. Overall, then, the book is to be commended for tackling both the philosophical issues at stake in research design as well as the 'nuts and bolts' (or 'brass tacks') of actually doing research.

One of the book's touted selling-points is its focus on phases of research that precede data collection. That is, the book aims to train students not only in research methods, but also in the critical tasks of theorizing problems, generating research questions, and designing scientific inquiries - what the author refers to as 'thinking like a researcher.' This is certainly a welcome addition to a textbook on research design, and ought to help students to overcome some familiar stumbling blocks that seem to present themselves during graduate programs.

Because of its breadth, however, parts of the book can sometimes seem thin and underdeveloped. In particular, the chapters on data collection (specific research methods) are less detailed and comprehensive than other books manage to provide. It is hard to give a detailed 'how to' guide to either survey research, experiments, case studies, or interpretive methods in just 10 pages. As a result, instructors will almost certainly want to supplement this book with more detailed material, perhaps tailored to their specific discipline.

Even so, this book is an excellent backbone for an undergraduate or graduate class on research methods. It will have to be read in conjunction with discipline-specific guides to conducting research (and, most likely, alongside examples of good and bad research), but this does nothing to detract from the book's own value: it will certainly offer a valuable overview of key concepts, ideas, and problems in research design and data-collection, and will serve students throughout the duration of their studies and not just for one class.

This book is accurate, error-free, and as unbiased as it is possible to be in the social sciences. Of course, it is possible to imagine those who simply hold different views about what social science "is" or should be; some scholars might bristle at the notion that only knowledge produced according to the narrow strictures of the scientific method can be considered "scientific knowledge," for example, while others might balk at interpretivism being given parity of esteem with what they see as more rigorous methodological practices. But for the broad mainstream of the social sciences, there will be little in this book that stands out as unusual, controversial, or one-sided.

On the whole, the content of this book will remain relevant for a long time. After all, the basics of the scientific method and the fundamentals of research design seem unlikely to change in the foreseeable future. New and cutting-edge strategies of data collection and theory-testing do emerge, of course, but these are probably best delivered to students in the form of discipline-specific books or articles that could be assigned to complement this textbook, which deals more with foundations than it does with current debates.

The book is organized well and information is presented in a clear way. The prose is accessible and each chapter proceeds methodically.

This text is certainly consistent, and proceeds according to a methodical and logical structure. Key terms and concepts are introduced early on, and there are no 'surprises' in later chapters.

This book is organized into chapters, each of which could be used as the keystone reading for a given class session, and each chapter is broken down in easy-to-digest sections, making the book as accessible as possible. The fact that there are 16 chapters mean that the book could support 16 separate class sessions - that is, just enough to orient classroom discussion for an entire semester. That said, each module does not comprise sufficient material for a whole week; the chapters will need to be supplemented with extra reading material, especially in graduate seminars. It is unlikely that instructors will want to assign only part of a given chapter. Overall, the text reads well as a whole and in terms of its individual chapters.

The chapters for this book are organized into five sections: the introductory section, a section dealing with the basics of empirical research, sections on data collection and data analysis, and a final section that deals with ethics in research. This is a sensible and logical structure for the book, and nothing seems out of place. Again, the book is an accessible and smooth read; it will pose no challenges to an informed reader, and there will be nothing in the organization of the book that will be distracting or irritating.

As a single PDF, this book is easy to navigate.

I noticed no spelling or grammatical errors in this well-written book.

I can detect no culturally insensitive or offensive remarks in this book.

It is worth mentioning that this text ought to serve students well throughout their undergraduate studies, graduate careers, and beyond. It is a timeless - if necessarily limited - resource, and be returned to again and again.

Reviewed by Tamara Falicov, Associate Professor, University of Kansas on 8/21/16

The book is divided into sixteen chapters, which seemed a bit intimidating at first. I later realized that they are not necessarily very long chapters; it varies in terms of the topic. This makes the book quite comprehensive in that the book could be used for the length of the semester, one chapter per week. This is a useful model and one can add or subtract if needed. For example, the beginning chapter which discusses what science is and uses vocabulary from the hard or natural sciences may not necessarily be relevant in a social science course, but the author is being comprehensive by explaining the origins of science and the creation of the scientific method.The vocabulary in bold is extremely effective throughout the book.

The book is meticulously researched and I did not note any egregious statements or inaccuracies. There was one strange sentence when the author was trying to contrast a liberal to a conservative’s viewpoint on page 18 that made this reader feel a bit uncomfortable in how one ideological viewpoint was portrayed, but I’m not sure it was necessarily bias; perhaps just the writing was a bit heavy handed

The book makes sure of updated case examples, discusses how students utilize the internet for research, etc. The theories outlined here are the classic important debates, and the breadth of knowledge the author imparts is extremely comprehensive and up to date. this book could definitely stand on its own for many years before changes in the field might necessitate updating.

I found the textbook to be a refreshing read. The writing is very accessible and clear, but can be dense at times (though not in a problematic way—it means that with some of the more challenging material, the students will have to dig a little deeper to glean the information. The writing was very crisp, and to the point.

The book is written in a careful, consistent manner. As mentioned earlier, the vocabulary words in bold are consistent signposts, and there are citations (not too many, not too few) that help structure the book and provide a cogent framework. Sometimes there are summaries and bullet points, and other times there aren’t, so this is not exactly consistent, but it doesn’t detract from the overall work.

The chapters are excellent stand alone essays that could be used interchangeably. Some of them, such as the first chapter, is historical and philosophical, but not essential to understanding social science research methods. The second and third chapters are excellent for the researcher who is just starting out to formulate a research question. It helps them to think about the various theories and approaches available to them in terms of the angle, focus and methodology selected. The later chapters explain in greater detail various kinds of methods such as how to measure constructs, and scale reliability. These are higher order concepts which would be useful to graduate students—chapters 1-3 could not only work for graduate students, but also for upper division undergraduates.

The book was structured in a logical progression. There were no problems there. There was some repetition with various terms such as Occum’s razor, but this is because there is some overlap with concepts which I think is fine, given that some chapters may not be used in the course of a semester.

No problems with typeface, the diagrams and graphs are incredibly useful in breaking down more complex research methods.

There were no problems with syntax, grammar, spelling that I came across, except for a minor typo in chapter 9 in the table of contents.

I felt that the author was careful in his selection of case students to try to be inclusive and culturally sensitive. There was that one sentence that raised eyebrows about liberals versus democrats that I mentioned previously, but it wasn’t a major deal.

I found this book to be extremely useful and of high quality. I will to recommend it to a colleague who is teaching research methods next semester in a different department.

Reviewed by Yen-Chu Weng, Lecturer, University of Washington on 8/21/16

Dr. Bhattacherjee’s book, Social Science Research, is a good introductory textbook for upper-level undergraduate students and graduate students to learn about the research process. Whereas most research methods textbooks either focus on “research design” or on “data analysis”, this book covers the whole research process – from theories and conceptual frameworks to research design, data collection, and analysis. This book is structured as four modules and is very adaptable to instructors who want to teach any portions of the book.

Social science is a quite diverse field, including studies of socio-economic data, human behaviors, values, perceptions, and many others. Not only are the topics wide-ranging, but the research methods and the underlying philosophy of science also vary. Therefore, it is extremely difficult to write a textbook that includes everything. Dr. Bhattacherjee’s book is a nice overview of all these different methods commonly used in the social sciences. It aims for breadth, but not depth. Once could use this book as an entry to the field, but would need to seek additional resources for specific methods or analytical skills.

Based on my review of the book, the content is accurate, error-free and unbiased. However, better consistency with terminology often used in other related fields (such as statistics) would lessen students’ confusion with concepts.

Research methods are not time-sensitive topics and are not expected to change much in the near future. The inclusion of some cases or examples showcasing how social science research methods can be applied to current events or topics would help illustrate the relevance of this book (and social science research).

The book is very clear and accessible. It’s written in a way that is easy to understand. Important terminologies are bolded and these are good signposts for key concepts. A glossary summarizing definitions for the key terminologies would help students understand these key concepts. The book includes some helpful figures illustrating concepts in research design and statistics.

Overall, the book is very consistent.

The author, Dr. Bhattacherjee, structured the book following the research process – from theories, to research design, data collection, and analysis. Each module can be a standalone unit and is very adaptable to instructors who want to teach with either the whole book or individual modules. Although each module is mostly self-contained, it is impossible not to refer to other chapters since research is an iterative process. However, I do not expect this to be a huge problem for someone who wants to teach only a section of the book.

The fact that this book is structured as modules also makes it expandable. For those who want to teach only the philosophy of science or only the research design portion, they can add more details and in-depth discussion to these topics.

The book is well-organized and flows well with the research process. The chapters are clearly titled as well as the subheadings. Some numbering with the subheadings would help with navigation. In addition, a chapter summary/conclusion would also help with summarizing the main concepts of a chapter (some chapters do have a summary, but not all chapters).

The flow of the first module (Introduction to Research) is sometimes confusing – the book jumps between big ideas (scientific reasoning, conceptual framework) and specific details (variables, units of analysis) several times in the first four chapters. I thought that reorganizing the chapters as Ch1, Ch4, Ch3, Ch2 would flow better (from big ideas to specific details).

Since the book is organized by the research process, not by the type of research (qualitative vs. quantitative), Module 3 (Data Collection) and Module 4 (Data Analysis) cover both types of research. As a result, the flow/connection between each chapter are less clear. By reorganizing these two modules into “qualitative research methods and data analysis” and “quantitative research methods and data analysis”, not only would improve the flow of the book, but also better serve researchers who are interested in a particular type of research.

There are no major problems with the book’s interface. Each chapter is clearly titled. I would like to see the subheadings being numbered as well. If the PDF could have the Table of Contents on the sidebar, it would improve the navigation even more.

There are no grammatical errors noticed.

There are no culturally insensitive or offensive materials noticed. The few examples used in the book are very general and not controversial.

This book is a nice walk-through guide for researchers new to the field of social science research. One thing I would recommend adding is examples and cases. With more examples and cases, students would be able to put research methods into context and practice how they can apply the methods to their own research projects.

Reviewed by Dana Whippo, Assistant Professor of Political Science and Economics, Dickinson State University on 1/7/16

For its purpose, as introduced by the author, this is appropriately comprehensive. However, it is much more brief, more concise, than traditional research methods texts for undergraduates – which the text does not claim to be. It lays a sufficient foundation, with room and expectation for the professor to supplement with additional materials. Supplementing would be important if using this in an undergraduate classroom. I appreciate that the author emphasizes the process of research, and takes the time to address, in the first four chapters, the logic and process of research in a way that allows the text to be used in multiple disciplines. Indeed, this is one of the strengths of the book: that it can be used broadly within the social sciences. The text does not provide either an index or a glossary. This is more challenging when planning for its use in an undergraduate research methods class; however, I think that the strengths of this book outweigh the weaknesses.

I have not noticed any errors or bias. The only issue I’ve noticed, as indicated in other parts of the review, is depth. Doctoral students would bring in a sufficient foundation for reading this on their own; undergraduates will need scaffolding and additional resources to competently understand the complexity inherent in research.

The content does not read in a way that seems (either now or in the future) likely to read as dated or obsolete. The discussion of survey methodology and analysis programs will change with technology, but that should be easy to update. One of the book’s strengths is its focus on the foundation of research methods: the relationship between theory and observation, the understanding of science, and the logic that underlies the process of research.

The book is well-written and concise. Bearing in mind the author’s stated target audience of graduate and doctoral students, it is entirely reasonable that this would require additional work and instructor support (extra time and explanations for definitions and examples, for instance) when used in an undergraduate classroom.

The terminology is consistent throughout.

Faculty would be able to easily divide the text into smaller sections, which would be useful as those smaller reading sections could be combined with targeted supplementary materials.

The topics generally flow well as presented; the only exception is having the section on research ethics at the end. However, this chapter would be easy to assign earlier in the semester.

I did not have any problems with respect to interface issues.

I did not notice any grammatical errors that interfered with the reading process.

I did not notice any offensive comments or examples. The book is brief by design; it does not include the numerous examples that populate the traditional undergraduate research methods text. I did not find it offensive or insensitive.

Reviewed by Andrew Knight, Assistant Professor of Music Therapy, Colorado State University on 1/7/16

I have not seen a more comprehensive text for this topic area, and yet it retains a concision that I would have appreciated as a PhD student when I took courses in research methods. I think that the text may lend itself to several different types of courses. The early chapters can by used for more theoretical research courses, especially for new researchers and fundamentals of research courses. The later chapters can be used for "nuts and bolts" courses for addressing specific methodological issues. The appendices are an especially nice touch and added value for faculty to understand how the author uses this text and creates a syllabus to complement it.

There are very few typographical errors, and overall, the text is rigorously unbiased in its scientific method claims and explanations.

The overwhelming majority of the content in this text is classical understandings of research and methodologies that are essential to all graduate students, particularly in business and the social sciences. There is no indication that any of the content will suffer from claims that it is obsolete or irrelevant.

The clarity of the text is sound partly due to the concision of the book. Shorter chapters, easily navigable paragraphs, and other compositional devices make the text accessible to most levels of graduate students. The bolded words invite the reader to create a self-guided glossary, not any different than a textbook in an 8th grade student collection, which is helpful to counter the sometimes sophisticated nature of research theory.

No consistency issues noted.

The chapters have a nice flow to them, and can be "chunked" out for use in more beginner or more advanced courses. One preference of this reviewer would be to assign the ethics in research chapter earlier in the course calendar, and thus earlier in the textbook, so it is part of the foundational aspects of understanding social science inquiry. Meanwhile, the qualitative and two separate quantitative chapters play well together for students who will want to review them before exams or after the course is finished while they pursue a thesis/dissertation.

Again, I think the ethics chapter should be earlier, but that is simply a personal choice and can be altered by my syllabus. One issue that I wonder if graduate students might prefer is if they are not already 13 chapters into a text/course and only then are they getting to a basic concept such as measures of central tendency. Offering some of the nuts and bolts of research methods earlier in the text and tying them into the more theoretical concepts might help with clarity of flow for the typical graduate student.

No issues, nice charts and graphics throughout.

Very few noted.

This text is not insensitive in any way. As a matter of fact, pointing out historical issues in research ethics using some sensitive vignettes actually heightens the importance of research in everyday life.

I'm looking forward to adopting it for courses and using it for my own reflections on research!

Reviewed by Allison White, Assistant Professor, Colorado State University on 1/7/16

This text covers a wide array of topics relevant to social science research, including some that are not traditionally included but are welcome additions, such as a chapter dedicated to research ethics. A sample syllabus for a graduate course on research design is also offered at the end of the book, facilitating course development. The book is comprehensive in its treatment of the central components of research design and the different methodological strategies that researchers can leverage to investigate various research questions. Notably absent, however, is an index, glossary of terms, or questions for discussion, which are frequently included in textbooks devoted to research design.

The content is accurate and unbiased, which may be particularly important for texts on research design, as many fields within social science are intractably polarized between quantitative and qualitative approaches. The book goes a long way toward bridging that gap by treating the multitude of methodological orientations fairly and without obvious preference for one or another.

This book will stand the test of time due to its comprehensiveness and fair and balanced approach to research design. Both cutting-edge and classic approaches to research are discussed and the book may be easily updated as warranted by important developments in the social sciences.

The text is written clearly and accessibly, providing adequate context for most of the jargon and technical terminology that is covered. For this reason, it seems suitable for a variety of graduate-level courses, including research design survey courses and more advanced courses focusing on specific approaches.

The text is internally consistent in terms of terminology and framework.

The book neatly compartmentalizes the topics, making it easily divisible into smaller reading sections that can be assigned at different points within the course. The individual chapters stand on their own and do not require contextualization. Numerous sub-headings throughout each chapter flag the central themes.

The topics in the text are presented in a logical, clear fashion. The topics build productively throughout the textbook, beginning with the basic concepts of research design and culminating with different strategies to approach research.

The book's interface is seamless. Charts and images appear appropriately sized and undistorted and the text is free from navigation problems.

The text does not contain conspicuous grammatical errors.

The text and examples provided in it are not culturally insensitive or offensive in any way. Examples are drawn from universal theories rather than research that is culturally-specific.

Reviewed by Jim Hutchinson, Lecturer, University of Minnesota on 6/10/15

This text covers all the basic concepts expected in a book on social science research. However, it does so at a fairly superficial level. The author says this was intentional in order to provide coverage of essential topics and not distract students. As such, the book seems to do a good job introducing all the essential concepts for graduate research, but supplemental materials are likely needed depending on instructor or student needs.

The book seems to free of errors and bias.

Social science research isn't likely to change greatly so this text should remain relevant for some time and can easily be updated to accommodate new techniques as they arise.

The book is generally well-written and accessible. The writing is clear and there are sufficient examples to help students grasp concepts.

The text appears consistent with others in the field.

The text may be best used as an overview of the research process in social sciences rather than a reference. However, various chapters could also be used alone or as supplement to other materials and excluding chapters not relevant to a particular course should not cause any issues. The author even mentions excluding certain chapters that are actually full courses where he teaches.

The organization and sequence seems very logical.

I accessed the PDF version and did not experience any issues with text or graphics.

I think a good proofread would help. There are a number of places where extraneous words were left in (perhaps when rewriting and changing the structure of a sentence) or where words are not quite right. For example:

"...a researcher looking at the world through a “rational lens” will look for rational explanations of the problem such as inadequate technology or poor fit between technology and the task context where it is being utilized, while another research[er] looking at the same problem through a “social lens” may seek out social deficiencies..."

Such errors are not really problematic but they are a bit distracting at times.

I did not find the book to be insensitive or offensive. Examples used are fairly benign. For example, when discussing the tendency of lay people to view a scientific theory as mere speculation the author uses an example of teacher practice instead of a more charged example such as evolution.

Overall, this is a good book to introduce graduate (and even undergraduate) students to social science research. It is not comprehensive enough to be the only text students encounter, but it would be sufficient for say master's level programs that focus more on capstone or practical "informed by research" projects. Students planning to conduct original research, analyze data and interpret results will likely find this insufficient.

Reviewed by Paul Goren, Professor, University of Minnesota on 7/15/14

This text introduces social science doctoral students to the research process. It can be used in sociology, political science, education public health, and related disciplines. The book does an excellent job covering topics that are too often neglected in research methods classes. Standard texts devote most of their attention to different modes of data collection (e.g, lab experiments, field experiments, quasi-experiments, survey research, aggregate data collection, interpretive and case study methods, etc.). This book covers these materials but also devotes a lot of time to steps in the research process that precede data collection. These steps include formulating a research question, concept definition, theory elaboration, measurement (including reliability and validity) and sampling. There is also cursory coverage of descriptive statistics and inferential statistics (a chapter on each) as well as chapter on research ethics. In terms of coverage, then, the text can be described as comprehensive in terms of topics. In terms of depth of coverage of the topics, the text takes a minimalist approach. That is, the fundamentals of each topic are covered, but there is little discussion beyond the basics. Teachers looking for the perfect text that nails all the key points should look elsewhere or make heavy use of supplements. For instance, in the discussion on concepts, constructs, and variables, the text does not distinguish between latent variables, which are unobservable, and manifest variables, which are observable, as is common in the structural equation modeling tradition used in sociology and psychology. This is a minor omission and there are others one might quibble with. The bottom line is that most key topics in the research process are covered, but the coverage is not terribly deep.

From what I can tell, the book is accurate in terms of what it covers. There are some things that should probably be included in subsequent revisions.

The social science research process is unlikely to change in any signfiicant way for some time; therefore, I suspect the book will be relevant for years to come. The key will be ensuring that the latest research trends/improvements/refinements are added to the book. For instance, internet sampling techniques have come a long way over the past decade and there are now pollng firms that can admister online surveys to representative samples of the broader U.S. population. So long as the author keeps on these develops, this will serve as a useful introductory text for the foreseable future.

This text is extremely and unusually well-written and clear. This is one of the text's greatest selling points. No complaints on this score.

The book is very consistent from what I can see.

This book can work in a number of ways. A teacher can sample the germane chapters and incorporate them without difficulty in any research methods class.

The organization is fine. The book presents all the topics in an appropriate sequence.

The interface is fine. I didn't experience any problems.

I didn't see any errors, it looks fine.

The book is not culturally offensive.

Teachers looking for a text that they can use to introduce students to the research process and cover the foundational components of the research process should find this manuscript sufficient for their needs. Simple additions on slides or class room commentary can easily take care of the various omissions that pepper the text. Indeed, one could use this text in conjunction with discipline specific supplements quite effectively. For instance, in chapter 3 on the research process, the author devotes 5 paragraphs to common mistakes in the research process, such as pursuing trivial research questions or blind data mining. I can see how psychologists, sociologists and political scientists could provide discipline-specific examples to tailor this to their students particular needs. More generally, I suspect that the text could be used in conjunction with germane discipline specific materials quite effectively in research methodology classes. The book is not perfect. I wish there was more discussion on field experiments in the experiment chapter. Other than a brief mention that these are relatively rare, there was nothing. These are indeed relatively rare but that seems to be changing in some fields (e.g. economic, political science), and I think more discussion of this technique is warranted. The chapter on case study methods would benefit from discussion on the historical and comparative methods that are used in various social science disciplines, as well as some discussion on case selection methods. The statistical coverage is very thin and should not serve as the primary source material in any class that covers statistics. For instance, the discussion on the empirical assessment of reliability (for items or scales) does not discuss in depth the assumptions that underlie the various methods nor the modifications that need to be made across different levels of measurement. To take another example, the author presents the formulae for the variance and standard deviation on p. 122 with the customary n-1 in the denominator. Students often ask me why we divide the mean squared deviation by n-1 instead of n, which is what we do for the mean. Professors will need to make sure that their slides include discussion of the degrees of freedom idea and perhaps some discussion on unbiasedness as well. In the inferential statistics chapter there's no discussion on desirable properties of estimators (unbiasedness and efficiency). This is an unfortunate oversight. These could be added very easily using simple graphs. One thing that's lacking is a chapter on statistical graphics. The book makes great use of graphics and other visual aids throughout the chapters, but I wish there as a standalone chapter that introduces simple plots for univariate and bivariate data. This can be supplemented easily enough, but the omission seems odd. Again, this book can serve as an compact introduction in a graduate research methodology class for students across the social sciences, but it would work best in conjunction with deeper and more discipline specific materials prepared by the professor.

Reviewed by Anika Leithner, Associate Professor, California Polytechnic State University on 7/15/14

This text certainly covers all the basic concepts and processes I would expect to find in an introduction to social sciences research. What I liked in particular is that the author includes information on the ENTIRE research process, including critical thinking and research ethics, in addition to the "nuts and bolts" of research such as operationalization, data collection, and data analysis. I also find it useful that the author includes sections on both qualitative and quantitative research, which is great for an introductory level course. In general, readers can expect to find information on theory- and hypothesis building, operationalization/measurements, sampling, research design, various data collection strategies (e.g. surveys, experiments, etc.), as well as data analysis. The primary reason I did not give this text 5 stars is that the author does not provide a great amount of detail for a lot of the book's sections. He explains in the preface that he purposefully chose to reduce the text to the basics in order to keep the text compact and clutter-free. In general, I tend to agree with this approach, as so many methodology textbooks seem to get lost in examples and case studies without clearly illustrating the research process as a whole. However, as I was reading through this book, I kept thinking that I would need to supplement multiple areas of this book with more information in order to make it truly accessible to my students. To be fair, I think that A) anyone who has taught methods before would be able to use the "bones" of this book to prepare students sufficiently well for class and then easily fill in the blanks, and B) it appears that this text was written primarily with graduate students in mind, whereas I most teach undergraduates. In all, I still think that this is a great free alternative to many textbooks out there, but if your teaching style depends on your text including a lot of explanation and examples (or even applications), then this is likely not the text for you. Finally, this book does NOT include an index or a glossary. Personally, I did not find this to be a problem, as the outline/table of contents is very useful, but perhaps students using the text could benefit from an index that would allow them to quickly look up what they need to know.

I did not detect any errors or any purposeful bias in this textbook! Some readers might find that the author's choice of terminology does not necessarily match what I would consider standard practices in the broader social sciences (e.g. the use of the term "mediating variables" instead of "intervening variables"), but it is always clear what the book is referring to and it shouldn't be too difficult to bridge this "terminology gap." Occasionally, I was a bit puzzled by a definition or an explanation. For instance, the author states that "control variables" are not pertinent to explaining the dependent variable, but need to be taken into consideration because they may have "some impact" on it. I'm assuming the author means that they are not pertinent to the hypothesis being tested (as opposed to them not being pertinent to the explanation of the dependent variable). This type of ambiguity does not occur very often in the textbook and it does not necessarily represent an error. It merely seems to be an issue of miscommunication. Overall, I very much liked this text for its accuracy.

Luckily, research methods do not change drastically in a short period of time, so I expect the longevity of this book to be very high. In my experience, the biggest factor that can make a research text outdated is the use of up-to-date examples and case studies. This text includes very few of either, so I think this text could be used for many years to come.

The book is very clear and accessible, probably largely due to its minimalist approach. Aside from the above-mentioned deviations from broader social sciences terminology on a few occasions, I did not encounter any problems with the jargon/technical terminology used. The only minor problem I noted (which made me I've a ranking of 4 as opposed to 5) was a certain amount of repetitiveness in the earlier chapters, specifically with regard to positivism/post-positivism and the discussion of theory/hypothesis creation and testing.

The book is very consistent. It has a clear outline that matches the natural research process and the author very consistently adhere to this outline. Chapters naturally flow from one another and are logical.

This book is very well organized and easily accessible due to its division into logical chapters and sub-sections. In addition, the author highlights important concepts in bold, making it even easier to follow along. I would have no problem assigning smaller reading sections throughout the quarter/semester.

As mentioned above, the text is very well organized and flows naturally/logically. It follows the research process from critical thinking, conceptualization, to operationalization/measurements, research design, data collection, and data analysis. Research ethics are discussed in an appendix/addendum.

There are no major problems with the book's interface. Occasionally, graphs and tables are not as crisp and visually appealing as they might be in an expensive textbook, but personally, the ability to assign an open source text to my students far outweighs any concerns I might have about the visual attractiveness of a book. This text is easy to read and quite user-friendly.

I detected no grammatical errors.

The text includes very few examples and it is hard to imagine how research methods in general could be offensive to anyone (unless it is the practice of science itself that offends them), but for completeness' sake, allow me to state that I found no instances of insensitivity or offense in this textbook.

This text covers all the basics of the research process. It does not contain a lot of the "bells and whistles" that the expensive traditional textbooks have (e.g. lots of examples, fancy graphs, text boxes with case studies and applications, etc.), but it certainly gets the job done. Personally, I appreciate the compact nature of this text and I would much rather fill in a few gaps on my end, if it means that I can assign my students an open textbook.

Reviewed by Brendan Watson, Assistant Professor, University of Minnesota on 7/15/14

See overall comments. read more

See overall comments.

Dr. Bhattacherjee's "Social Science Research: Principles, Methods, and Practices," is a comprehensive, but a bare-boned (and generic) introduction to social science research. In this case "generic" is actually a positive attribute: because the text covers social science research broadly, rather than sociology, psychology, etc. specifically, this text can easily be adapted to the needs of basic research methods courses in allied disciplines. (I teach an introductory quantitative research course for master's and Ph.D. students in a School of Journalism & Mass Communication). I describe the text as comprehensive, because if my students got a basic grasp of all of the concepts in the book, they'd be well positioned to continue on to more advanced research courses (though the text is less valuable as a reference than more comprehensive introductory texts). But while Dr. Bhattacherjee's introduction says that the book is bare-boned by design -- "I decided to focus only on essential concepts, and not fill pages with clutter that can divert the students' attention to less relevant or tangential issues" -- some topics deserve more attention. For example, Institutional Review Boards (IRB) receive only two short paragraphs, and there is no mention of the history of why such boards were deemed necessary and play an important role in the research process. I'd consider such knowledge essential for students, and this is the type of information I would like a text to focus on so that I can spend class time reviewing more complicated concepts students might have trouble grasping on their own. (Generally I found the writing to be approachable, and concepts to be well explained, though extensive examples are also part of the "clutter" omitted from this book). Another topic I would have liked to see developed further - and perhaps is especially important to the more digitally-savvy crowd interested in the open textbook movement - is the expanding role of the Internet and digital technologies in the research process itself, particularly in the era of "big data." The text, for example, mentions Internet surveys, but there is no conversation about tools one can use to build an Internet survey; how Internet surveys differ from traditional modes of surveying; or the practice of weighting Internet survey results to make them "representative" of the larger population. That said, I am balancing using this text versus a more comprehensive, but much more expensive, commercially produced text. Another thing that this book is missing are instructional resources that commercial publishers provide, but ultimately by using this text I can contribute to creating greater value for my students. However, it would have to be supplemented heavily with other materials, as well as lectures, which is not without a trade-off cost. It's certainly doable, but ultimately means a greater investment of my time, and I have to weigh investing my time in creating hands-on learning opportunities and providing students with thorough feedback on their work with the time I'd have to invest in using a text that is complete, but needs to be much more heavily supplemented with additional materials. Ideally, several faculty with similar teaching needs would team up to combine and adapt several open texts to their courses' needs. Adapting and supplementing this text for my purposes by myself, however, remains a steep, if not insurmountable task for a tenure-track professor. This text, however, is thorough enough to maintain my interested in trying to find a way to make it work.

About the book.

Part I. Main Body

Science and scientific research
Thinking like a researcher
The research process
Theories in scientific research
Research design
Measurement of constructs
Scale reliability and validity
Survey research
Experimental research
Case research
Interpretive research
Qualitative analysis
Quantitative analysis: Descriptive statistics
Quantitative analysis: Inferential statistics
Research ethics

Ancillary Material

This book is designed to introduce doctoral and postgraduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioural research, and can serve as a standalone text or as a supplement to research readings in any doctoral seminar or research methods class. This book is currently being used as a research text at universities in 216 countries, across six continents and has been translated into seven different languages. To receive updates on this book, including the translated versions, please follow the author on Facebook or Twitter @Anol_B.

About the Contributors

Anol Bhattacherjee is a professor of information systems and Citigroup/Hidden River Fellow at the University of South Florida, USA. He is one of the top ten information systems researchers in the world, ranked eighth based on research published in the top two journals in the discipline, MIS Quarterly and Information Systems Research , over the last decade (2001-2010). In a research career spanning 15 years, Dr. Bhattacherjee has published over 50 refereed journal papers and two books that have received over 4,000 citations on Google Scholar. He also served on the editorial board of MIS Quarterly for four years and is frequently invited to present his research or build new research programs at universities all over the world. More information about Dr. Bhattacherjee can be obtained from his webpage at http://ab2020.weebly.com .

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Social sciences in crisis: on the proposed elimination of the discussion section

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Published: 09 August 2023
Volume 202 , article number 54 , ( 2023 )

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The social sciences are facing numerous crises including those related to replication, theory, and applicability. We highlight that these crises imply epistemic malfunctions and affect science communication negatively. Several potential solutions have already been proposed, ranging from statistical improvements to changes in norms of scientific conduct. In this paper, we propose a structural solution: the elimination of the discussion section from social science research papers. We point out that discussion sections allow for an inappropriate narrativization of research that disguises actual results and enables the misstatement of true limitations. We go on to claim that removing this section and outsourcing it to other publications provides several epistemic advantages such as a division of academic labour, adversarial modes of progress, and a better alignment of the personal aims of scientists with the aims of science. After responding to several objections, we conclude that the potential benefits of moving away from the traditional model of academic papers outweigh the costs and have the potential to play a part in addressing the crises in the social sciences alongside other reforms. As such, we take our paper as proffering a further potential solution that should be applied complimentarily with other reform movements such as Open Science and hope that our paper can start a debate on this or similar proposals.

Authorship conflicts in academia: an international cross-discipline survey

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1 Introduction

Social sciences are currently facing several interrelated crises, such as the replication crisis, the theory crisis, the applicability crisis, the generalizability crisis, and the validity crisis. These crises potentially threaten numerous aspects of the social scientific programme and the public perception of social science (Benessia et al., 2016 ; Hendriks et al., 2016 ). To this date, numerous potential solutions have already been proposed, ranging from changes in scientific norms to statistical training. Our focus is to present an additional, as-of-yet unrecognized potential solution, namely directly reworking the structure of academic papers. Specifically, we propose eliminating the discussion section from research papers. Our central claim is that eliminating discussion sections might improve the social science primarily because authors will have less opportunities for presenting their research in a biased way, leading to adverse downstream effects. We argue that removing the discussion section from papers and instead outsourcing it to independent discussion papers might eliminate many of the cognitive biases that make the discussion section problematic while not presenting substantial new costs. We further claim that this proposal can draw on several additional upsides, such as benefiting from the division of labour and from an adversarial mode of scientific progress. We see this proposal as working alongside, and not replacing, other reform efforts, and hope that the present paper kickstarts a debate on the merits and costs of the current structure of academic articles.

This paper is structured as follows. In Sect. 2 we briefly introduce the crises facing the social sciences and discuss current solutions. In Sect. 3 we show why these crises matter for social science and society more generally and how this points towards two distinct challenges. In Sect. 4 we develop our proposed solution of eliminating the discussion section and defend it against objections.

2 Social science in crisis

In this section we give a short upshot of the so-called ‘crises’ facing the social sciences. We focus on three central ones: the replication crisis, the theory crisis, and the applicability crisis; though what we say also applies to several others, such as the theory crisis and the validity crisis. Furthermore, our paper does not aim to address fraud per se, we are focused on less severe but still essential issues that arise in academic conduct.

Issues related to the replication crisis have been investigated thoroughly by social scientists, metascientists, and philosophers (e.g., Anvari and Lakens, 2018 ; Fletcher, 2021 ; Flis, 2019 ; Lilienfeld and Strother, 2020 ; Wiggins & Christopherson 2019 ). This debate was kickstarted in response to a replication failure of social priming findings (e.g., Bargh et al., 1996 ), which triggered several large-scale collaborative replication attempts. For example, the Many Labs Replication Project found only roughly 36% (Klein et al., 2014 ) and 54% (Klein et al., 2018 ) of studies to replicate respectively—leading to the proclamation of a ‘replication crisis’. Footnote 1

Another crisis that has been identified is the ‘theory crisis’, that various social sciences face a “lack of a cumulative theoretical framework” (Muthukrishna & Henrich, 2019 , p. 221) and that theories not just methods have shaky foundations leading to failure of generalisation and replicability more broadly (Eronen and Bringmann, 2021 ; Fiedler, 2017 ; cf. Fried, 2020 ; Maatman, 2021 , Others have proclaimed an ‘applicability crisis’, which is motivated by the claim that scientific findings are not as readily applicable as the scientific literature suggests. For example, when findings from the ‘nudge’ literature have been applied in large-scale contexts, they often failed to replicate or replicated only at a substantially reduced effect size (see e.g., Della Vigna & Linos, 2020 ). Based on these findings, some have argued that the social sciences as a whole are not (yet) in a position to give confident actionable advice and are thus in an applicability crisis. Footnote 2

Several underlying causes of and potential solutions to these crises have been identified. One such cause is publication bias (Renkewitz & Keiner, 2019 ), that statistically significant results are the deciding factor for publication (Franco, Malhotra, & Simonovits, 2014 ). A further cause is the prevalence of questionable research practices, or QRPs (Fiedler & Schwarz, 2016 ), which are scientifically misguided but socially acceptable practices that compromise the integrity of scientific conduct. Other causes are selective analysis of some variables, dropping of experimental conditions, additional data collection after data analysis, warped incentives, and bad statistical (Gigerenzer, 2018 ) or measurement training (Lilienfeld & Stroher 2020 ).

Several potential solutions have been proposed under the banner of ‘Open Science’. For instance, some have argued that preregistration can provide a strong counterbalancing force by making QRP’s harder to execute and thus forcing researchers to adhere to pre-stated statistical analyses (Nosek et al., 2018 ). Others have proposed a new submission format of ‘registered reports’, in which only the hypotheses and the design of the study are subjected to peer-review and, if accepted for publication, result in a guaranteed publication irrespective of the findings. This solution has already been adopted by several journals (e.g., Chambers, 2013 ; Eder & Frings, 2021 ; Hardwicke & Ioannidis, 2018 ; Keil et al., 2020 ). Others have suggested better statistical education and reform in social science departments to remedy the statistical and methodological causes of the crises (e.g., Gigerenzer, 2018 ; Lakens, 2019 ).

In this paper, we want to draw attention to another potential partial cause of these interlinking crises and propose a solution to it that has not yet been picked up. Specifically, we argue that the structure of academic papers contributes significantly to the current situation of the social sciences, and that eliminating the discussion section promises to substantially contribute towards allaying at least some of these problems. Importantly, we see this solution as working in tandem with the other science reform efforts. Furthermore, we do not claim that our proposal is without drawbacks, and we offer a comparative argument by showing that its benefits outweigh its costs, and that it might meaningfully contribute to reforming social science. Before we move on to our discussion of this proposal in Sect. 4 , we want to state the importance of this project and focus on two central challenges facing social science research in Sect. 3 which then will be addressed by our suggested reform.

3 Why this crisis matters?

The first aim of this section is to outline the scientific and societal consequences of these crisis. Our ultimate aim is to set up two challenges for conducting social science research in the current social structure of publication and public communication. We divide this section into (Sect. 3.1 ) concerns about public communication and trust in science and (Sect. 3.2 ) concerns about achieving the epistemic aims of science, specifically concerning the incentive structure of social science research.

3.1 Science communication: trust in social sciences

In analysing why these crises matter, we are focusing first on effective science communication and public trust. Trust in science matters because, as Wilholt ( 2013 ) states, “[p]olicy-makers, legislators, investors, and activists, as well as ‘ordinary people’ in their capacities as citizens or consumers frequently rely on the results of science, trusting […] these will help them make well-informed decisions” (Wilholt, 2013 , p. 234). One should differentiate science-to-science communication from science communication to the general lay public. Footnote 3

We want to start with the latter. Especially the replication crisis has directly entered the public discourse, including ample media coverage Footnote 4 . As Fetterman and Sassenberg ( 2015 ) contend, the replication crisis is bound to have negative reputational effects on science. Recently Hendriks et al. ( 2020 ) showed that study credibility and researcher trustworthiness increase significantly if a study was successfully replicated and decreases otherwise (cf. also Mede et al., 2020 ). Wingen, Berkessel & Englich ( 2019 ) showed that low replicability specifically reduces trust in psychology. As such, the replication crisis already directly impacts science communication and consequently becomes important for scientific testimony (Gerken, 2015 , 2020 ). This is because, as Whyte and Crease ( 2010 ) argue, one important project for a philosophy of science is to “facilitate trust between scientific experts and ordinary citizens” (cf. also Irzik and Kurtulmus, 2019 ; Whyte & Crease, 2010 , p. 411) This project seems especially relevant against the background of wide-spread denial of various scientific findings. Footnote 5 However, the crises directly indicate that some of the present public distrust might be warranted, making public communication increasingly challenging by making differentiation of the levels of credibility of findings difficult. Thus, the crises impose a serious challenge to science communication as not to lose public trust in science overall, which would by itself lead to further negative outcomes such as a failure to comply with public health messaging.

Second, this problem of trust reaches beyond public science communication. It likewise concerns science-to-science communication, and as such directly impacts epistemic matters. As Romero ( 2019 ) argues, a social science in crisis can lead interdisciplinary research astray, which is especially troublesome for philosophy, since “empirically informed philosophers, and specifically moral psychologists, have relied heavily on findings from social psychology. They also need to clean up their act” (Romero, 2019 , p. 7).

A further area in which the crises discussed here impact science-to-science communication is within scientific collaborations. There are good reasons to think that in many scientific disciplines trust can be more epistemically basic than empirical evidence, indicating that decreasing trust could undermine scientific knowledge production, going against the very epistemic aims of science (cf. Hardwig, 1991 ). Specifically, in an age of ‘Team Science’ (Ledford, 2015 ), scientific research largely relies on collaborations, which in turn depend on trust in the scientific community. This is because individual researchers in a collaborative project often have only partial information and expertise in a specific area, making trust a crucial element for successful collaboration (Bird, 2010 ; Fricker, 2002 ; Gerken, 2015 ). As such, it has been argued (De Ridder, 2022 ) that the erosion of trust due to events such as the replication crisis and the discovery of a widespread use of questionable research practices, might cause an can impede effective collaborations within scientific teams, ultimately hindering the production of scientific knowledge.

3.2 Achieving the epistemic aims of science

The epistemic aims of science have been a topic of ongoing debate; the most prominent proposals include truth (Khalifa, 2022 ), knowledge (Williamson, 2002 ), and understanding (De Regt, 2017 ). Footnote 6 Some claim that the aim is objectivity or proclaim a value-free ideal of science. But even if such ideals are too ambitious, as Haack ( 2003 ) argues, explicitly and systematically aiming at reducing the biases of the individuals involved in knowledge producing processes is one of the main constitutive features of science. The consensus is that, at least in the long run, science should be error-correcting (cf. Laudan, 1981 ; Mayo, 2005 ; Peirce, 1958 ).

The aforementioned crises point towards a concerning epistemic defect in our scientific methodology and as such to an obstruction in achieving the epistemic goals of science. We argue that one major factor for at least partially improving the state of social sciences comes from resolving a specific tension between the epistemic aims of science and the non-epistemic goals of individual scientists. We ultimately argue that the current structure of academic research papers is such that those aims are misaligned and that such a misalignment contributes at least in part to the crises facing the social sciences. We go on to claim that our proposed solution can, in tandem with other reforms, contribute to solving this structural problem. In what follows, we present the problem of misalignment in order to properly set up the remainder of the paper.

Already in the 1960s, Polanyi ( 1962 ) argued that scientific cooperation emerges to a large extent as an unintended consequence of the social structure of science. This idea became especially prominent in the sociology of science (Barnes & Bloor, 1996 ), building on the thesis that the social features of science emerge from self-interested actions of individual scientists. This bottom-up process of explaining scientific norms was picked up by various philosophers of science, such as Kitcher ( 1990 ) and Strevens ( 2011 ) in what was termed the economics of science (cf. also Stephan, 2012 ). The central claim is that it is beneficial for promoting the aims of science if the aims of individual scientists align with the epistemic aims of science, while a misalignment can cause epistemic malfunctions of various types and severities.

The most straightforward way to achieve alignment is by having individual scientists engage in their research practices for reasons that align with the epistemic aims of science anyway—scientists might conduct research because they themselves want to get at the truth (i.e., the epistemic aim of science). However, scientists are also (and sometimes primarily) motivated by non-epistemic aims, such as advancing their career, getting recognition, or receiving grants. We can call such personal non-epistemic aims credit (Boettke & O’Donnell, 2016 , p. 11; Zollman, 2018 ).

In publishing, credit seems to be at least one primary aim. Today, high publishing frequency in high-ranking journals is the main currency of success on the academic job market and in the grant system across disciplines. Still, the same publishing practices that give scientists credit might after all align with the aims of science. For instance, if publishing credit is a reliable indicator for scientific performance and having higher performing scientists on higher positions is on average epistemically advantageous for the scientific enterprise, then the career goals of individual scientists and the aims of science align. That such an alignment is important for the emergence of successful scientific norms and is indeed very frequently in place, is one of the main arguments of both Kitcher ( 1990 ) and Strevens ( 2011 ).

However, there are numerous reasons to think that this alignment might not be as straightforward as sometimes assumed. We argue that the crises discussed above point towards a tension between the aims of science and the credit aim of scientists. Others, who recognize a similar conflict, such as Hackett ( 2005 ) and Sovacool ( 2008 ), argue that publishing practices overemphasize novelty. Heesen ( 2018 ) argues that the credit system in science publishing incentivises speed and impact at the cost of reproducibility, pointing directly to a connection with the replication crisis. Fidler and Wilcox ( 2018 , Sect. 4.5) suggest in accord with Vazire ( 2018 , p. 416) that the aim of protecting one’s own professional reputation often motivates resistance to the self-correcting nature of replication (cf. also Fetterman and Sassenberg, 2015 ). Plausibly, science has already developed strategies to align the non-epistemic aims of scientists with the epistemic aims of science. Footnote 7 This typical alignment strategy consists of [AM] an adversarial mode Footnote 8 of science research and [IS] linking it with the individual incentive structure.

We want to start by explaining AM . Scientists, like all humans, are plagued with blind spots, biases (Pashler & Wagenmakers, 2012 ), prejudices, fall prey to rationalization (Schwitzgebel & Ellis, 2017 ), are fooled by cognitive artefacts (Machery, 2017 ), or are faced with suboptimal incentives (Pashler & Wagenmakers, 2012 ). Thus, it is paramount to put scientific findings under a high level of scrutiny. The general idea is to balance the blind spots of one scientist with the knowledge of another, challenging the biases and prejudices of one scientist by others with different flaws. In general, this is done by scrutinizing the findings one scientist holds dear by others who have no incentives to prefer that particular method or theory. Footnote 9 In this paper, we essentially argue for an extension of the adversarial mode that is already deeply entrenched in science and scientific practice, and which also appears in various foundational theories of scientific methodology. For instance, it underlies very prominently the Popperian philosophy of science (Popper, 1934 Footnote 10 )—especially the idea that we want to try our best to falsify scientific hypothesis under very rigorous conditions. Footnote 11

A prime example for the adversarial mode of science is peer-review. Ideally, in peer-review, papers are put under high scrutiny by anonymous experts in the respective domain and only those papers who survive the most stringent of reviews will be accepted or invited for revision. However, the challenge for the adversarial mode in peer-review and elsewhere is this: Why would anyone ever want to put themselves under such scrutiny, especially if one’s career depends on it? We now want to introduce the second part of the alignment strategy, i.e., linking the adversarial mode with the incentive structure of individual scientists. Consider peer-review again. Today, it usually brings with it much higher reputation to publish peer-reviewed than non-peer reviewed articles (Csiszar, 2016 ), and it typically brings with it a substantially higher reputation to publish in journal with very stringent standards than with moderate standards. Footnote 12 This can be inferred from the fact that, nowadays, almost all current high-ranking journals list their (high) rejection-rate as a quality criterion which shows a perceived link between an adversarial mode and quality. On this basis, some countries have official rankings of journals which are drawn upon in hiring and promotion circumstances, as is the case in Finland where the Publication Forum classification system explicitly ranks journals. Footnote 13 As such, researchers who put their work under stronger adversarial scrutiny and succeed obtain more credit, and thus the self-interested scientists’ career-goal and the epistemic aims of science align (at least, if the system works as intended).

This concludes our discussion of how the alignment strategy should work in practice. In this section, we argued that the epistemic aims of science rely on bias reduction and self-correction—features deeply associated with study replication. The sociological analysis of the incentive structure of science suggests that epistemic achievements of science can be diminished if the self-interested career-goal of scientists and the epistemic aims of science are misaligned. In this context, we presented a typical alignment strategy consisting in an adversarial mode of science research and linking it to the individual incentive structure. In the next section, we show how the current structure of scientific papers works against the presented alignment strategy, how this results in contributing to the crises of social science, and how this problem might be resolved in an as of yet unexplored way.

4 A further cause and a proposed solution: the elimination of the discussion section

In this section, we first (Sect. 4.1 ) identify an unexplored potential contributor to the interlocking crises facing social science: the structure of academic articles. We claim that the way researchers (are expected to) structure their research articles might set them up to engage in behaviours that feed into the crises and exacerbate other epistemic defects: Solving this necessitates structural changes. In Sect. 4.2 , we then go on to propose a potential structural solution to this cause and argue that research in the social sciences might benefit from an elimination of the discussion section in papers. Arguing based on the alignments strategy as discussed in Sect. 3 , we claim that this holds primarily because it reduces biases and possibilities to portray one’s own research in a favourable but incorrect light, and further sets up an incentive structure for researchers to critically examine research of others via the novel proposed vehicle of a discussion paper, both of which jointly promise to contribute towards addressing the state of crisis the social sciences find themselves in. In Sect. 4.3 , we discuss potential objections to this project and conclude with a summary of the costs and benefits of this approach.

4.1 The epistemic faults of a discussion section

Academic articles in the (social) sciences have roughly four main sections in addition to an abstract and a conclusion: (i) introduction and literature, (ii) methods, (iii) results, and (iv) discussion. The introduction sets up a problem, motivates the hypotheses, and contextualises the research. The methods section states the procedures, the sample selection process, and all further design implementation steps. The results section summarises all results and reports them in tables, graphs, and written form as well as though additional numerical in-text descriptions. In the discussion section, the results are put into context and conjectures as to the generalisability, limitations, and applicability of the findings are laid out (Bazerman, 2004 , pp. 207–208). Specifically, it is in the discussion section that researchers provide verbal interpretations of their data by summarising the main findings and drawing attention to what they take to be the central take-away. They then frequently state limitations of both statistical and methodological nature and provide caveats to both these limitations and the findings presented in the paper. Depending on the discipline, this is followed by a rough outline for the practical applications of these findings by individuals, governments, or institutions.

The focus of our proposal is the discussion section. Historically, the discussion section in this modern form has been a consistent and recognisable part of academic papers for around 100 years. Atkinson shows that while historically, experimental papers during the 17th and early 18th century were largely “unelaborated, miscellaneously organized, and relatively narrative in character” (Atkinson, 1998 , xxiv), by 1775, some predecessors to a discussion section were already present in recognisably similar form. By the 19th century, the rough structure of a theoretical part followed by the experiment followed by a discussion was relatively common, and by 1925 it had become “the standard” it is now (Atkinson 1998 , 70; cf. also Bazerman, 1985 ).

We claim that this structure of academic articles carries with it several epistemic flaws that have prohibited science from functioning as well as it otherwise might have. Further, we argue that this structure may also have directly and indirectly contributed to the set of crises. Specifically, we claim that discussion sections directly foster behaviours that rest upon epistemically dubious grounds, such as enabling researchers to set the narrative of their results, allowing them to put the focus on certain results, and enabling them to self-report the limitations they see in their own design. These behaviours all fall prey to cognitive biases such as the choice-supportive bias, post-hoc rationalization, ostrich effect, bias blind spot, or the hindsight bias. Additionally, this system is perhaps best characterised as consisting of several perverse incentive structures. As such, researchers are less likely to honestly report the data, their resultant true implications, and the applicable methodological drawbacks. This current situation runs contrary to the alignment strategy as presented in (II), since for these behaviours to be in accord with the epistemic aims of science, all researchers would have to be immune to these biases of various types and would further have to exhibit an unreasonably high degree of selflessness. This, we claim, is unlikely. Footnote 14

Let us discuss those shortcomings one by one. First, in the discussion section, researchers can put into focus easy-to-explain data that fit their narrative while dropping entirely the data that do not fit or that are even counter to the proposed narrative. This behaviour is often a clear ethical violation of research conduct (cf. Greenwald, 1975 ). However, it is yet incentivized by standard publishing practices that reward presenting to the editor and reviewers a paper with a clear narrative that neatly fits all the data rather than a paper where the overall story is less clean but closer to the actual results. Doing the latter reduces the prima facie chances of publication: This is why researchers often use the discussion section to draw attention to the data that do fit their narrative and the hypotheses reported, while sweeping those parts that would make the paper less convincing under the rug (or into the appendix, which is sometimes located online behind several steps to ensure that it cannot be easily accessed, if at all). This is a clear misalignment of individual self-interested incentives and the aims of science. It results in a net negative impacting on science as it is, through directly promoting selective reporting. It also negatively impacts science communication more generally as discussion sections fail to be accurate representations and explanations of the data collected.

One might object that this is only a minor problem since scientists are aware that the discussion section is bound to epistemic defects. It is probably true that an increasing number of scientists are becoming aware of the issue, however, not all readers in the academic sciences possess the requisite level of proficiency to assess the specialized data, and this is especially difficult for science reporters and in collaborative and interdisciplinary research. Generally, even for scientists who are well aware of the potential for bias in discussion sections, it can pose major difficulties to separate out the true findings from the noise, particularly if the discussion section is very persuasive or engaging. Therefore, switching to a less biased system is preferable to relying on the awareness of the readers.

Second, researchers are also asked to state the limitations of their research design in the discussion section. This, while on the face useful as the authors are plausibly best positioned to identify where the weaknesses of their research design are and which corners have been cut, is equally problematic because this again leaves it up to the discretion of the researchers themselves to point out limitations. One need not come up with far-fetched scenarios to imagine researchers downplaying the trade-offs that they had to take in their experimental design and the resultant limitations of the results. On top of that, these sections are also often accompanied by a short explanation for why these limitations do not fully apply to the design reported and why they ought not be taken as too impeding (to both the publishability of the research and the widespread adoption of the finding). Researchers may then be more likely to not honestly state the full extent of the limitations, either because they themselves are suffering from cognitive biases that make it hard to see their work in an objective light, or, more likely, because they have incentives not to do so as they seek publication as well as public praise and recognition. Though this practice can sometimes be rectified by the peer-review system through its adversarial element, we claim that often, researchers understate the limitations of their own research to the detriment of science and public trust more generally in a way that is hard to evaluate from a sporadic peer reviewer’s perspective. Moreover, this problem is made worse by university press offices, that often continually overstate the findings reported and discussed in discussion section to an even greater extent than the authors themselves, making the problem even worse by extending it directly into the science-to-public communication front.

To combat these shortcomings of the discussion section, there are guidelines from journals and professional societies that outline best practices for what goes into a discussion section and how to properly engage with one’s own data. The concern is, however, how to incentivize researchers to follow such guidelines and to effectively self-police. Both worries discussed above have in common that for science to function properly, researchers would have to act against their career-guiding publishing aims by honestly discussing non-conforming data and by openly stating the true limitations of the design, making it increasingly unlikely that this is indeed happening at a large scale. As such, it runs contrary to our proposed alignment strategy - missing the adversarial pillar. Changing dishonest or biased behaviour is unlikely to come about without addressing the underlying defective misalignments of individual self-interested aims and the aims of science and cannot as such be laid at the feet of individual researcher’s responsibility, but rather must be solved systemically and in tandem with existing reform efforts.

4.2 Removing the discussion section

These shortcomings have not gone undetected (e.g., Barbour, 2015 ; Edwards and Roy, 2017 ). However, we proffer a novel solution: the wholesale elimination of the discussion section from academic papers. This brings with it not only a (partial) redress of the original problems outlined in Sect. 4.1 , but might also lead to various additional theoretical and practical upsides that themselves impact the final cost-benefit analysis of this proposal. We see this structural change as working alongside other science reform efforts and not as a standalone solution; in fact, it may lack much of its potential benefits if other aspects of the scientific process are not improved upon. To begin with, let us consider how eliminating the discussion section might promise to address the outlined challenges.

First, removing the discussion section directly addresses the problems of researcher incentives in relation to the discussion of non-confirming data and serious limitations as there is simply no more discussion section to do this in. In our model, research articles introduce a problem, state their (preferably pre-registered) hypotheses clearly (Introduction), present the design (Methods), and report their (preferable analysis-plan based) findings (Results). In such a model, researchers are no longer able to selectively discuss their data or limitations in the discussion section, and it would be significantly more difficult to have these sentiments appear in other sections of the paper. Interacting with other approaches and solutions, such as pre-registration or analysis plans, researchers would be further incentivized to outline all their data as stated in the pre-registration/registered report. Without having a place in each research paper in which researchers are heavily incentivized to misrepresent their contributions, understate their limitations, and overplay their practical importance, there is significant reason to believe that the misalignment is, at least to a significant extent reduced. We argue that doing so will not only be better for science but might also be preferred by researchers as they are then able to conduct their scientific work more straightforwardly, with less of an incentive to oversell their results, thus reducing inner personal conflicts where present. Note that this move is more akin to reducing the opportunities to do harm and thus indirectly reducing the incentives.

That being said, any structural changes of this magnitude will have unforeseeable consequences. One risk might be that researchers, no longer being able to frame their results as they please in their discussion sections, will simply move to misstating their data. While we cannot rule this out, our argument for this proposal does state that it can only be expected to have substantial positive impacts if it is implemented in conjunction with other reforms like pre-registered analysis plans. Due to the fact that Open Science initiatives, such as pre-registered analysis, specifically target questionable research practices related to statistical analysis within the data section, it is a much more difficult task to shift bias towards this section than expressing the bias in the discussion section. While researchers may resort to extreme measures such as manipulating the data itself, if they are willing to go to such lengths, it is unlikely that they are not already doing so within the current system. As such, while there is a potential that researchers move their bias from the discussion section to the data section, we at least can be confident in the minimal claim that without the discussion section, the misalignment will be reduced (though is unlikely to be eliminated).

Additionally, we claim that most of the upside of our proposal will be cashed out by our second proposal of a novel type of academic article as a replacement of the discussion sections: a discussion paper. Footnote 15 Discussion papers are papers designed to discuss one or more original research articles (or the data presented within them). They are aimed at contextualising the findings, outline future research questions, and analyse limitations that allow careful interpretation of the results and appropriate practical guidance. Contrary to the current format, where only researchers themselves write the discussion section, discussion papers can be written by a different set of researchers (that may or may not include the authors of the paper reporting the data), thus directly drawing on the better epistemic ability of researchers to evaluate others’ work in an unbiased way. Specifically, having discussion papers written by somebody other than the researchers has the epistemic upsides of resulting in (i) personal bias reduction, (ii) a utilisation of the division of academic labour (potentially across disciplinary boundaries), (iii) an introduction of novel incentives in line with the adversarial mode of scientific research, and (iv) an improvement of science communication downstream. Footnote 16 Let us tackle those upsides in turn.

(i) Outsourcing the discussion section to papers not written by the authors of the original papers plausibly reduces personal biases across the board by using our proposed alignment strategy. This is because the authors of the discussion section do not share the same incentive structure and personal involvement with the original research. They are in a less biased position to evaluate how the data fit into the bigger picture and what the actual limitations are. Outsourcing the discussion section thus allays some of those worries and promises an incentive structure that is less likely to coincide with cognitive biases to produce subpar scientific results. In simple terms, it helps the scientists align their personal incentives with the goals of science. This is plausibly even the case when the authors of the discussion section are the authors of the original empirical work since the publication of their data no longer depends on their framing of them in the discussion section, at least partially reducing the personal biases in play.

There is a potential risk that separating the discussion section from the main article may amplify the problems associated with an integrated discussion section. It might be argued that authors now have more incentive to make the discussion paper attention-grabbing, leading to a misalignment of personal aims and the epistemic aims of science. However, we believe that the peer-review process can help mitigate this risk. In the current system, a biased discussion section may receive less scrutiny since the referees have to divide their focus and may prioritize getting research published simply because the data is important even if the quality of the discussion section is subpar. In contrast, in a system with a separate discussion paper, all scrutiny of the referees is focused on the quality of the discussion paper alone. Therefore, while we cannot completely rule out the possibility of a new set of bad incentives, we argue that the peer-review process is now in a better position to ensure the integrity of the discussion paper.(ii) Splitting off the discussion section from the primary data papers also allows academic research to directly harness the fruits of the division of labour in a majority of cases. Specifically, our proposal might result in an altered research landscape where those who are especially apt at designing and conducting studies do so, while those with a more generalist skill set synthesise several such results into discussion papers, perhaps along an experimentalist-theorist divide that is already seen in other disciplines. This advantage is especially striking against the backdrop of Cohen’s ( 1990 ) observation that in psychology, researchers frequently misinterpret p-values and Ziliak & McCloskey’s ( 2008 ) contention that empirical researchers generally too often draw wrong conclusions regarding the statistical significance of their results. Dividing the labour between scientists who are specialised in conducting studies and scientists who are specialized in interpretation and synthesis promises an improvement that might help address the crises facing the social sciences while also plausibly boosting scientific productivity. Additionally, this division of labour may even be beneficial across disciplines. For example, consider a philosopher writing up a discussion paper of research on moral judgements in addition to a similar paper being written by a psychologist. Both types of discussion papers would bring a different skill set to bear on the available data which may then allow readers to get a perspective on the data that would otherwise be inaccessible. Additionally, cross-disciplinary division of labour within discussion papers might be especially useful, where authors from different disciplinary backgrounds collaborate on a single discussion paper, drawing on research from several disciplines to allow for a more balanced and holistic picture of scientific research in a given area of study. This, so we argue, would greatly improve scientific progress within, but also between disciplines.

We take our proposal to improve upon the incentive structure to better align the credit incentives and the epistemic aims of science. This contrasts with the previous model in which authors were incentivised to portray their studies as without serious limitations and as providing actionable recommendations for policy makers. The revised model improves this by reducing perverse incentives, leaving authors with less reason and less opportunities to act contra the aims of science, at least concerning interpretation, limitations, and applications of the research. Further, having an adversarial relationship between those writing the discussion papers and those writing the data focused papers does not only eliminate or reduce the worry of bias and perverse incentives, it also independently improves the epistemic environment of researchers by removing epistemically unfavourable elements that make researchers prone to self-deception (cf. Heyman et al., 2020 ). This then directly interlinks our suggestion with previously proposed solutions to the crises facing the social sciences. Since the peer-review process will be focused entirely on the design and results for research papers and entirely on the merit of the discussion for discussion papers, this incentivises authors of experimental papers to pre-register their data and make their data sets open accessible, as these practices are now directly conducive to publication success, interlinking this proposal directly with other Open Science reform efforts. Further, the novel discussion papers themselves will have a distinct incentive landscape, in which authors might be more likely to discuss limitations and applications of research more honestly as portraying these data in a good light is at least not central to their success in publishing.

Finally, this solution promises to improve public communication of scientific findings. Usually, public science reporting draws on the interpretations of scientific studies by making them easier digestible for a general audience. After all, page-long regression tables are often not what can be communicated to the public. However, since the incentive structure of the standard discussion section motivates overstatement and distortion of the empirical findings, these defects get passed on directly to the public. This not only leads to potential misinformation, but if some of those overstatements are recognized, it may also lead to an increase in general mistrust in scientific findings. Since our proposal reduces problematic incentives, and thus promises to decrease overstatement and distortion of findings, it promises to improve public communication of scientific findings as a consequence. Of course, it may be that science journalists will not engage with the discussion papers meaningfully; after all, they are already likely to skip the discussion section. We argue that while this is true, the mere existence of and potential institutional prestige of high-quality discussion papers may also make it more likely to journalists to pick them up and report on them. This may then take less the form of a sensationalist piece on a specific finding, but rather more general summaries of the state of the scientific field. Moreover, these discussion papers will still allow journalists to pick out specific findings that translate well into a headline, but the whole paper itself will arguably be more likely to contribute to a more balanced and nuanced depiction of the science.

Given these advantages of splitting research papers into two parts, this should give academic journals some incentive to switch to such a mode. As argued in (Sect. 3.2 ), an adversarial mode is already valued in current publishing to increase journal reputation. Thus, journal publishers could benefit from seriously considering our proposal to further increase their reputation, making this proposal also plausibly implementable in the short term. Here is what we specifically propose: Journals ought to disallow the use of a discussion section (and its contents) in their primary research articles which would only be consisting of an introduction, a methods section, a results section, and a conclusion. They would then also start to accept manuscripts of ‘discussion papers’. These discussion papers discuss the data of one or multiple primary research papers. Authors of these research papers would then be asked to critically discuss the data by pointing out limitations of the designs, highlighting potential applications, drawing out interesting follow-up opportunities, and synthesising the results in the wider literature. This is markedly different from the current system and a radical change, but one that promises to contribute to improving social science alongside other reform efforts.

4.3 Objections and concluding remarks

We close this section by considering several objections before giving a brief comparative argument of the benefits and costs of our proposal. First, one might argue that the discussion sections themselves are not the fundamental cause of any of these crises. This, so the objector, is because what is truly driving the challenge is the overall incentive structure of science, and as such, the overall incentive structure ought to be identified as the cause and be addressed directly. On this line of reasoning, proposing to eliminate the discussion section would be akin to merely treating a symptom and thus failing to actually address the root cause. While this assessment might be partly correct, its conclusion does not follow. From the claim that the problems with the discussion section ultimately stem from the overall incentive structure facing scientists it does not follow that eliminating the discussion section is misguided. Rather, addressing one aspect of this incentive structure related to the discussion section might go a long way towards affecting the overall structure in reverse.

As a second objection, one may object that the above approach relies on other solutions already being implemented successfully. Specifically, the proposal to publish research papers primarily consisting of methods and results might presuppose that data are being shared openly and freely according to Open Science best practices, as failing to disclose data open and freely merely shifts the problem of individual bias. We agree that eliminating the discussion section alone cannot solve the multitude of crises facing the social sciences and that it will most likely require a multiplicity of different reforms to have an effect. However, we do not see this as a problem as no single solution is capable of fixing the interlinking crises and argue that eliminating the discussion sections can play one part in addressing them.

Third, a downside of outsourcing the discussion section might be that some data of research papers might never be discussed. This can be frustrating for the researchers who published the research paper and want engagement with their findings. We reply that our model does not exclude the authors of the original research paper to also write a discussion paper on their data, though their discussions would then go through a separate peer-review process that would evaluate them solely on their contribution to the discussion (not the data collection). Furthermore, discussion papers are stand-alone publications and as such attach themselves to the already existing incentive structure for writing papers in general (i.e., credit). This encourages researchers to engage with data that is not theirs but it also allows engagement with one’s own data. It is, thus, plausible that we might even see more discussion of the data than we currently do. Moreover, authors of discussion sections have now an incentive to carefully study bulks of research papers, and editors and reviewers will additionally consider which one is worth discussing. This plausibly creates an environment that allocates the resources for discussion writing more efficiently than a system which rigidly limits itself to only one discussion of one research paper by the same researchers.

Fourth, one may object that the significant heterogeneity that is observed between disciplines with respect to replicability, questionable research practices, and the like may suggest that our framing (as well as our proposed solution) may not apply to all social sciences equally. In short, we think that this objection is roughly correct. It is the case that there are differences in replicability and publication of replications (e.g., Berry et al., 2017 ), which is something that forecasts continue to anticipate in the future (Gordon et al., 2020 ). As such, the elimination of discussion sections may have disparate effects across disciplines. However, we do not think that this is indeed an issue for our proposal as we do not think that discussion sections are the underlying cause of all the crises. Rather, as we have argued, we believe that removing discussion sections might have a net positive impact on some of the malaises facing some disciplines.

A fifth objection is that the proposed discussion papers create their own perverse incentives. It could be argued that the authors of the initial research paper would be very well positioned to immediately submit a discussion paper accompanying their first publication, effectively pre-empting further submission. This, so the objection, might lead to an unfair advantage on part of the original authors because they increase their likelihood at publishing more work in the limited journal space. We respond to this objection as follows: First, even if there is such an advantage for the original authors, in our proposed structure there is at least a reasonable chance for authors other than the original researchers to participate in a separate discussion of the data by publishing a discussion paper (perhaps by including additional data from other work). As such, our proposal might retain some perverse incentives, but they are arguably reduced. Second, if the previously sketched epistemic advantages of a division of labour hold, then at least some authors specializing in discussion papers will also have one advantage over the authors of the research papers who are not that specialized. As such, it is implausible that the authors of the original research papers will always be the ones who publish the discussion papers or will always end up the ones with the highest visibility, while it may also be the case that further, more expansive discussion papers discuss the data of any individual research paper, even if that paper’s authors have already published a standalone discussion paper.

A sixth objection is that even if our proposal was implemented, there might be a dearth of potential authors willing to write such a discussion paper. It is unclear, so the objection, what will motivate the work on discussion papers such that the academic credit system will incentivise authors to spend substantial effort towards writing these papers. We respond to this in two ways: First, as we have argued above, it is very likely that the majority of discussion papers will include authors that have authored (some) of the underlying experimental papers, thus providing intrinsic motivation to write them. Second, and more importantly, we think that in situations where authors do not write the discussion papers themselves, career incentives to publish in prestigious journals will most likely provide sufficient incentives for third-party writers to write these papers. We believe that such high-profile venues will exist just by the nature of there being venues that offer discussion papers, and some of these being ranked higher (on whatever metric). Polemically put, we have yet to see an academic system (be it universities, journals, etc.) that academics themselves have not turned into a prestige hierarchy, accompanied by a drive to be on top. We expect that this mechanism will extend to our proposal as well, incentivising the production of high-quality discussion papers. Furthermore, we add the following anecdote: The journal Data is a data-science journal that offers (among other options) two types of submissions: Data Descriptors and Reviews. The former outline and explain a data set, the latter “concise and precise updates on the latest progress made in a given area of research”. While this is not quite our proposal and it is not within the social sciences, we take this example of a proof of concept.

We have now outlined the benefits of our proposal and replied to objections. However, as most policy prescriptions, our proposal is not without potential drawbacks. After having spent significant effort above outlining the potential upsides of our proposal, there are several costs to consider. First, one central cost with our proposal is that we may lose the epistemic advantages of authors discussing their own data in some instances. Particularly, the authors of a study often have unique insights into their data that may not be immediately apparent to third-party researchers. This is especially true for studies that involve complex datasets. By outsourcing the discussion section to third-party authors, we may miss out on important nuances and insights that only the original authors can provide. Furthermore, the original authors may have access to additional data or information that is not included in the published study. This may include preliminary analyses, unpublished data, or insights gained through personal experience or interactions with study participants. Keep, however, in mind the, as we argued, significant epistemic cost associated with the traditional structure of academic papers. Therefore, it is important to weigh the potential costs and benefits of our proposal in a nuanced and comprehensive manner. Note further that this only partly applies since the original authors can still write discussion papers as well. It is expected, however, that on various occasions original authors will never write or be able to publish discussion papers relating to their research paper. In such cases, it is indeed a genuine cost of our proposal that stands in a trade-off with the epistemic advantages of our proposal, which we argue outweigh the costs substantially.

A second potential source of substantial cost that may be associated with our proposal is that implementing such a sweeping change is rife with uncertainties that are extremely difficult to resolve ex ante, and that this may lead to unintended consequences. However, this is a cost associated with most reform efforts, even though we cannot rule out backfire effects of one sort or another. Additionally, even if our proposal is met with acclaim, then it is to be expected that initially only a few journals will pick up on the idea, as has been the case with reforms such as registered reports (Chambers, 2013 ; Hardwicke & Ioannidis, 2018 ; Keil, Gatzke-Kopp, Horvath, Jennings, & Fabiani 2020 ). As such, the whole system is only reformed gradually and potential drawbacks, once properly identified, can be met along the way. Even if the trade-offs stay initially incommensurable, having a diversification of journals between those with our newly proposed structure and other which follow a more traditional publishing structure will over time get us a better outlook on the benefits and costs of our proposal and the current system.

Overall, do the benefits outweigh the costs? Throughout (Sect. 4 ), we have outlined several potential benefits as well as costs associated with our proposal. In short, our proposed structural reform might lead to substantial improvements in bias reduction efforts, better incentives, and scientific integrity overall. However, there are costs to this that have to be weighed against the benefits. such as we might lose the epistemic advantage of authors discussing their own data in some instance. A general risk of such a major reform is that it may lead to a new equilibrium of behaviours that end up having even worse incentive structures building on a whole new set of biases. As we have said before, we cannot be sure that this does not happen. However, we believe that, because we see our proposal as a proposal on top of already existing reform movements, and because any type of adaption will be gradual, that most of the costs may be manageable. Furthermore, if we consider such a maximally pessimistic forecast, we should also consider that the potential maximum value created by this proposal is extremely high, promising widespread improvements across the social sciences.

Lastly, let us return to the original question of the crises the social sciences are facing and the potential progress that elimination of discussion sections may make. We argue that eliminating the discussion section might contribute meaningfully to addressing these crises, though, as pointed out before, much of this has to happen alongside other reform efforts, and any such effort is not without costs. Having removed the discussion section from papers, research norms will have to shift regarding data presentation and availability, potentially in line with Open Science norms. Doing so might directly impact replicability concerns, as authors are now preparing their data sets for discussion papers (if they want their research to be included in future papers), thus aligning their incentives with those that would contribute to combating the replication crisis. Further, dedicated discussion papers would mean authors have no incentive to play up a study’s relation to theory. This will allow readers to be in an epistemically superior position to judge which empirical investigations ought to inform scientific theorising and which fail to meet these standards. This is again a marked improvement over the previous system that might contribute to addressing the theory crisis and by moving social science towards its goal of being a cumulative science in line with Muthukrishna and Henrich ( 2019 , p. 221) who argue that the theory crisis stems from a “lack of a cumulative theoretical framework”. Our proposal would make accumulating several empirical findings and investigating them at once holistically easier, making it more straightforward for further researchers to directly build upon it. Finally, removing the discussion section also removes most of the place in which authors can state the wide applicability of their research that, as argued above, is frequently overstated. Discussion paper authors would face a different set of incentives and would, as such, be more likely to accurately portray how some data could impact public policy or adaption in the private sector, and additionally would also be evaluated separately in peer-review, thus providing a plausible path to combating the applicability crisis. Finally, by combating overstatements of applicability and selective interpretations of findings, this will additionally lead to a more honest public communication of scientific findings, promising to reduce mistrust in science. As such, our proposal, in tandem with other reform efforts, promises to be one important contribution in addressing both concerns of the scientific crises and of science communication. We hope that our paper can start a debate on this (or similar) proposals.

Adjacent fields such as experimental philosophy fared better at around 70% (Cova et al., 2018 ), while an early replication project in economics replicated 61% of studies (Camerer et al., 2016 ). These failures to replicate have been detected in many other domains such as mortality salience (Klein et al., 2019 ), metaphorical priming (Shanks et al., 2013 ), or ego depletion (Hagger et al., 2016 ).

This applicability crisis has especially come to the fore during the COVID-19 pandemic. Social scientists argued that social science research ought to structure the policy response, e.g., concerning behavioural considerations of vaccine uptake (Kowal et al., 2020 ; van Bavel et al., 2020 , p. 460; WHO, 2020 ), while IJzerman concludes, however, that social science is not yet “mature enough” (IJzerman et al. 2020 , p. 1094) to offer advice to policy maker.

For further work on the applicability crisis, see Loyka et al. ( 2020 ) and Dennis ( 2013 ).

And potentially also separate it from science communication to public policy makers since they have their own political aims and frequently some level of expertise that is not expected of a lay audience.

These include: https://www.nytimes.com/2018/11/19/science/science-research-fraud-reproducibility.html , https://www.theatlantic.com/science/archive/2018/11/psychologys-replication-crisis-real/576223/ . Veritasium published a YouTube video titled “Is Most Published Research Wrong?” that reached 2.7 million views: https://www.youtube.com/watch?v=42QuXLucH3Q.

For instance, polling of U.S. adults on climate change shows an outright denial or at least denial of its human cause from somewhere between 32% (Saad, 2017 ) to 52% (Funk & Kennedy, 2016 ) of the population.

Various others, frequently related epistemic aims of science have been proposed, such as explanatory coherence (Lycan, 1988 ), predictive success (Forster, 2002 ; Forster & Sober, 1994 ), rational acceptability (Putnam, 1981 ), agreement/consensus (Kuhn, 1962 ), social-epistemic value (Khalifa, 2010 ) and empirical adequacy (van Fraassen, 1980 ).

A similar idea is present in Strevens ( 2011 , p. 6) who views the alignment of norms and individual motivation as one of the three important dimensions of how the social norms of science and individual interests relate.

A different, complimentary, strategy which we will not address here is independent confirmation . As Hacking ( 1983 ) points out, independent confirmation is one of the main contributors in differentiating valid results from mere artefacts of the testing apparatus or testing methodology.

Some philosophers (cf. Moulton, 1993 ) argue that an adversarial discussion style might create a hostile environment. Note, however, that the focus of such arguments is usually on the discussion-style in research presentation and less on an adversarial approach to testing and reviewing. Also note that an adversarial mode does not have to be interpreted as mistrust, cf. also Nosek et al. ( 2012 , p. 626).

Importantly, they explicitly cite replication as a quality criterion of science.

As an example for how the adversarial approach is explicitly put into practice see, for instance, Fischer et al. ( 2020 ) in experimental philosophy, where the members of a joint project are chosen because of their disagreements on the philosophical views in question. See also Clark and Tetlock ( 2022 ) for a proposal of ‘adversarial collaborations’ in which authors of different ideological backgrounds collaborate. While this is not what we see as the main challenge for social science research, it provides an additional example of this type of solution.

For an analysis of the merit of peer review, see Heesen and Bright ( 2019 ) and Schroter et al. ( 2008 ).

https://julkaisufoorumi.fi/en/evaluations/classification-criteria .

For instance, the results presented by Anderson et al. ( 2010 ) suggest that current incentive structures of science are hard to overcome for individual scientists even if scientists have the epistemic aims of science in mind.

Though there may be other solutions that emerge from a removal of the discussion section, and we believe that eliminating the discussion section is potentially worth it irrespective of the structure that emerges as a result.

Some of these upsides would also be present if the discussion paper was indeed written by the same authors (perhaps because they know their complex data set very well): This may still reduce personal biases (i) as the publication success of the reported data does not depend on the discussion section at all, and further collaboration (be it adversarial or not, cf. Heyman et al., 2020 ) may also lead to some of the other advantages (ii)-(iv).

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Acknowledgments

We gratefully acknowledge helpful comments and suggestions from Cory Clark, Charlotte Werndl, and two anonymous reviewers of Synthese.

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Schoenegger, P., Pils, R. Social sciences in crisis: on the proposed elimination of the discussion section. Synthese 202 , 54 (2023). https://doi.org/10.1007/s11229-023-04267-3

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How Pew Research Center will report on generations moving forward

Journalists, researchers and the public often look at society through the lens of generation, using terms like Millennial or Gen Z to describe groups of similarly aged people. This approach can help readers see themselves in the data and assess where we are and where we’re headed as a country.

Pew Research Center has been at the forefront of generational research over the years, telling the story of Millennials as they came of age politically and as they moved more firmly into adult life . In recent years, we’ve also been eager to learn about Gen Z as the leading edge of this generation moves into adulthood.

But generational research has become a crowded arena. The field has been flooded with content that’s often sold as research but is more like clickbait or marketing mythology. There’s also been a growing chorus of criticism about generational research and generational labels in particular.

Recently, as we were preparing to embark on a major research project related to Gen Z, we decided to take a step back and consider how we can study generations in a way that aligns with our values of accuracy, rigor and providing a foundation of facts that enriches the public dialogue.

A typical generation spans 15 to 18 years. As many critics of generational research point out, there is great diversity of thought, experience and behavior within generations.

We set out on a yearlong process of assessing the landscape of generational research. We spoke with experts from outside Pew Research Center, including those who have been publicly critical of our generational analysis, to get their take on the pros and cons of this type of work. We invested in methodological testing to determine whether we could compare findings from our earlier telephone surveys to the online ones we’re conducting now. And we experimented with higher-level statistical analyses that would allow us to isolate the effect of generation.

What emerged from this process was a set of clear guidelines that will help frame our approach going forward. Many of these are principles we’ve always adhered to , but others will require us to change the way we’ve been doing things in recent years.

Here’s a short overview of how we’ll approach generational research in the future:

We’ll only do generational analysis when we have historical data that allows us to compare generations at similar stages of life. When comparing generations, it’s crucial to control for age. In other words, researchers need to look at each generation or age cohort at a similar point in the life cycle. (“Age cohort” is a fancy way of referring to a group of people who were born around the same time.)

When doing this kind of research, the question isn’t whether young adults today are different from middle-aged or older adults today. The question is whether young adults today are different from young adults at some specific point in the past.

To answer this question, it’s necessary to have data that’s been collected over a considerable amount of time – think decades. Standard surveys don’t allow for this type of analysis. We can look at differences across age groups, but we can’t compare age groups over time.

Another complication is that the surveys we conducted 20 or 30 years ago aren’t usually comparable enough to the surveys we’re doing today. Our earlier surveys were done over the phone, and we’ve since transitioned to our nationally representative online survey panel , the American Trends Panel . Our internal testing showed that on many topics, respondents answer questions differently depending on the way they’re being interviewed. So we can’t use most of our surveys from the late 1980s and early 2000s to compare Gen Z with Millennials and Gen Xers at a similar stage of life.

This means that most generational analysis we do will use datasets that have employed similar methodologies over a long period of time, such as surveys from the U.S. Census Bureau. A good example is our 2020 report on Millennial families , which used census data going back to the late 1960s. The report showed that Millennials are marrying and forming families at a much different pace than the generations that came before them.

Even when we have historical data, we will attempt to control for other factors beyond age in making generational comparisons. If we accept that there are real differences across generations, we’re basically saying that people who were born around the same time share certain attitudes or beliefs – and that their views have been influenced by external forces that uniquely shaped them during their formative years. Those forces may have been social changes, economic circumstances, technological advances or political movements.

When we see that younger adults have different views than their older counterparts, it may be driven by their demographic traits rather than the fact that they belong to a particular generation.

The tricky part is isolating those forces from events or circumstances that have affected all age groups, not just one generation. These are often called “period effects.” An example of a period effect is the Watergate scandal, which drove down trust in government among all age groups. Differences in trust across age groups in the wake of Watergate shouldn’t be attributed to the outsize impact that event had on one age group or another, because the change occurred across the board.

Changing demographics also may play a role in patterns that might at first seem like generational differences. We know that the United States has become more racially and ethnically diverse in recent decades, and that race and ethnicity are linked with certain key social and political views. When we see that younger adults have different views than their older counterparts, it may be driven by their demographic traits rather than the fact that they belong to a particular generation.

Controlling for these factors can involve complicated statistical analysis that helps determine whether the differences we see across age groups are indeed due to generation or not. This additional step adds rigor to the process. Unfortunately, it’s often absent from current discussions about Gen Z, Millennials and other generations.

When we can’t do generational analysis, we still see value in looking at differences by age and will do so where it makes sense. Age is one of the most common predictors of differences in attitudes and behaviors. And even if age gaps aren’t rooted in generational differences, they can still be illuminating. They help us understand how people across the age spectrum are responding to key trends, technological breakthroughs and historical events.

Each stage of life comes with a unique set of experiences. Young adults are often at the leading edge of changing attitudes on emerging social trends. Take views on same-sex marriage , for example, or attitudes about gender identity .

Many middle-aged adults, in turn, face the challenge of raising children while also providing care and support to their aging parents. And older adults have their own obstacles and opportunities. All of these stories – rooted in the life cycle, not in generations – are important and compelling, and we can tell them by analyzing our surveys at any given point in time.

When we do have the data to study groups of similarly aged people over time, we won’t always default to using the standard generational definitions and labels. While generational labels are simple and catchy, there are other ways to analyze age cohorts. For example, some observers have suggested grouping people by the decade in which they were born. This would create narrower cohorts in which the members may share more in common. People could also be grouped relative to their age during key historical events (such as the Great Recession or the COVID-19 pandemic) or technological innovations (like the invention of the iPhone).

By choosing not to use the standard generational labels when they’re not appropriate, we can avoid reinforcing harmful stereotypes or oversimplifying people’s complex lived experiences.

Existing generational definitions also may be too broad and arbitrary to capture differences that exist among narrower cohorts. A typical generation spans 15 to 18 years. As many critics of generational research point out, there is great diversity of thought, experience and behavior within generations. The key is to pick a lens that’s most appropriate for the research question that’s being studied. If we’re looking at political views and how they’ve shifted over time, for example, we might group people together according to the first presidential election in which they were eligible to vote.

With these considerations in mind, our audiences should not expect to see a lot of new research coming out of Pew Research Center that uses the generational lens. We’ll only talk about generations when it adds value, advances important national debates and highlights meaningful societal trends.

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Kim Parker is director of social trends research at Pew Research Center

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Infected: Understanding the spread of behavior

Human beings are likely to adopt the thoughts, beliefs, and behaviors of those around them.

Simple decisions like what local store is best to shop at to more complex ones like vaccinating a child are influenced by these behavior patterns and social discourse.

"We choose to be in networks, both offline and online, that are compatible with our own thinking," explained Amin Rahimian, assistant professor of industrial engineering at the University of Pittsburgh Swanson School of Engineering. "The social contagion of behavior through networks can help us understand how and why new norms, products, and ideas are adopted."

Initially, researchers thought highly clustered ties that are close together in networks created the perfect environment for the spread of complex behaviors that require significant social reinforcement. However, Rahimian, alongside a team of researchers from Massachusetts Institute of Technology (MIT) and Harvard University, counter these ideas. Long ties, which are created through randomly rewired edges that make them 'longer,' accelerate the spread of social contagions. For example, in the age of social media, long ties can facilitate broader reach across different demographics and heterogeneous populations. Rather than just communicating with one's neighbor, one may also be connecting with someone in another state -- even another country.

By using mathematical and statistical methods, the researchers were able to analyze the rate of spread over circular lattices with long ties and show that having a small probability of adoption below the contagion threshold is enough to ensure that random rewiring accelerates the spread of these contagions.

"Mechanisms that we identify for spread on circular lattices remain valid in higher dimensions," explained Rahimian.

Similar network dynamics arise in the study of neural activity in the brain.

"We are interested in the implications of these results for a better understanding of network structures that facilitate the spread of bursting activity in various brain regions," explained Jonathan Rubin, professor in Pitt's Department of Mathematics.

This research suggests those wanting to achieve fast, total spread would benefit from implementing intervention points across network neighborhoods with long-tie connections to other network regions, explained Dean Eckles, associate professor of marketing at MIT.

"Further work could study such strategies for seeding complex behaviors," Eckles continued.

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Materials provided by University of Pittsburgh . Note: Content may be edited for style and length.

Journal Reference :

Dean Eckles, Elchanan Mossel, M. Amin Rahimian, Subhabrata Sen. Long ties accelerate noisy threshold-based contagions . Nature Human Behaviour , 2024; DOI: 10.1038/s41562-024-01865-0

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In the brain, bursts of beta rhythms implement cognitive control

Bursts of brain rhythms with “beta” frequencies control where and when neurons in the cortex process sensory information and plan responses. Studying these bursts would improve understanding of cognition and clinical disorders, researchers argue in a new review.

The brain processes information on many scales. Individual cells electrochemically transmit signals in circuits but at the large scale required to produce cognition, millions of cells act in concert, driven by rhythmic signals at varying frequencies. Studying one frequency range in particular, beta rhythms between about 14-30 Hz, holds the key to understanding how the brain controls cognitive processes—or loses control in some disorders—a team of neuroscientists argues in a new review article.

Drawing on experimental data, mathematical modeling and theory, the scientists make the case that bursts of beta rhythms control cognition in the brain by regulating where and when higher gamma frequency waves can coordinate neurons to incorporate new information from the senses or formulate plans of action. Beta bursts, they argue, quickly establish flexible but controlled patterns of neural activity for implementing intentional thought.

“Cognition depends on organizing goal-directed thought, so if you want to understand cognition, you have to understand that organization,” said co-author Earl K. Miller , Picower Professor in The Picower Institute for Learning and Memory and the Department of Brain and Cognitive Sciences at MIT. “Beta is the range of frequencies that can control neurons at the right spatial scale to produce organized thought.”

Miller and colleagues Mikael Lundqvist, Jonatan Nordmark and Johan Liljefors at the Karolinska Institutet and Pawel Herman at the KTH Royal Institute of Technology in Sweden, write that studying bursts of beta rhythms to understand how they emerge and what they represent would not only help explain cognition, but also aid in diagnosing and treating cognitive disorders.

“Given the relevance of beta oscillations in cognition, we foresee a major change in the practice for biomarker identification, especially given the prominence of beta bursting in inhibitory control processes … and their importance in ADHD, schizophrenia and Alzheimer’s disease,” they write in the journal Trends in Cognitive Sciences .

Experimental studies covering several species including humans, a variety of brain regions, and numerous cognitive tasks have revealed key characteristics of beta waves in the cortex, the authors write: Beta rhythms occur in quick but powerful bursts; they inhibit the power of higher frequency gamma rhythms; and though they originate in deeper brain regions, they travel within specific locations of cortex. Considering these properties together, the authors write that they are all consistent with precise and flexible regulation, in space and time, of the gamma rhythm activity that experiments show carry signals of sensory information and motor plans.

A chart from a study plots bursts of brain waves of varying frequency at specific times. The bursts are represented as warm colors against a the blue background. When there are low frequency bursts there aren't high frequency bursts and vice versa.

“Beta bursts thus offer new opportunities for studying how sensory inputs are selectively processed, reshaped by inhibitory cognitive operations and ultimately result in motor actions,” the authors write.

For one example, Miller and colleagues have shown in animals that in the prefrontal cortex in working memory tasks, beta bursts direct when gamma activity can store new sensory information, read out the information when it needs to be used, and then discard it when it’s no longer relevant. For another example, other researchers have shown that beta rises when human volunteers are asked to suppress a previously learned association between word pairs, or to forget a cue because it will no longer be used in a task.

In a paper last year, Lundqvist, Herman, Miller and others cited several lines of experimental evidence to hypothesize that beta bursts implement cognitive control spatially in the brain , essentially constraining patches of the cortex to represent the general rules of a task even as individual neurons within those patches represent the specific contents of information. For example, if the working memory task is to remember a pad lock combination, beta rhythms will implement patches of cortex for the general steps “turn left,” “turn right,” “turn left again,” allowing gamma to enable neurons within each patch to store and later recall the specific numbers of the combination. The two-fold value of such an organizing principle, they noted, is that the brain can rapidly apply task rules to many neurons at a time and do so without having to re-establish the overall structure of the task if the individual numbers change (i.e. you set a new combination).

Another important phenomenon of beta bursts, the authors write, is that they propagate across long distances in the brain, spanning multiple regions. Studying the direction of their spatial travels, as well as their timing, could shed further light on how cognitive control is implemented.

New ideas beget new questions

Beta rhythm bursts can differ not only in their frequency, but also their duration, amplitude, origin and other characteristics. This variety speaks to their versatility, the authors write, but also obliges neuroscientists to study and understand these many different forms of the phenomenon and what they represent to harness more information from these neural signals.

“It quickly becomes very complicated, but I think the most important aspect of beta bursts is the very simple and basic premise that they shed light on the transient nature of oscillations and neural processes associated with cognition,” Lundqvist said.“This changes our models of cognition and will impact everything we do. For a long time we implicitly or explicitly assumed oscillations are ongoing which has colored experiments and analyses. Now we see a first wave of studies based on this new thinking, with new hypothesis and ways to analyze data, and it should only pick up in years to come.”

The authors acknowledge another major issue that must be resolved by further research—How do beta bursts emerge in the first place to perform their apparent role in cognitive control?

“It is unknown how beta bursts arise as a mediator of an executive command that cascades to other regions of the brain,” the authors write.

The authors don’t claim to have all the answers. Instead, they write, because beta rhythms appear to have an integral role in controlling cognition, the as yet unanswered questions are worth asking.

“We propose that beta bursts provide both experimental and computational studies with a window through which to explore the real-time organization and execution of cognitive functions,” they conclude. “To fully leverage this potential there is a need to address the outstanding questions with new experimental paradigms, analytical methods and modeling approaches.”

Paper: to understand cognition—and its dysfunction—neuroscientists must learn its rhythms.

Study reveals a universal pattern of brain wave frequencies

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Social sciences research (SSR) is an enterprise that is continuously evolving, but not without some debilitating issues that impede the realization of its full potential and usefulness. SSR, as a human initiative and activity, is discussed. The paper features the current methods and authorship issues that enhance the research outcomes' validity.
Social Science Research
Inequality in the relationship between educational expectations and educational attainment across academic achievement. Samuel H. Fishman. Article 102747. View PDF. Article preview. Read the latest articles of Social Science Research at ScienceDirect.com, Elsevier's leading platform of peer-reviewed scholarly literature.
Social Research
ISSN. 0037783X. EISSN. 1944768X. SUBJECTS. Sociology, Political Science, Social Sciences. COLLECTIONS. Arts & Sciences X Collection, JSTOR Archival Journal & Primary Source Collection. Most issues of Social Research address a single theme, which is addressed by scholars, writers, and experts from a wide range of disciplines.
Journal of Applied Social Science: Sage Journals
The Journal of Applied Social Science publishes research articles, essays, research reports, teaching notes, and book reviews on a wide range of topics of interest to the social science practitioner. Specifically, we encourage submission of manuscripts that, in a concrete way, apply social science or critically reflect on the application of social science.
Latest articles from The Social Science Journal
Employment and tourism: New research perspectives in the social sciences. edited by C. Guibert and B. Reau, Cham, Switzerland, Springer Nature, 2023, €44.99 (paperback), ISBN 9783031316593. Limin Ke, Guichao Jin, Yixuan Yang & Zhenqi Hu. Published online: 20 Dec 2023.
The Top 25 Social Science & Human Behavior Articles of 2023
Here, the authors show that levels of glutamate and GABA in the supplementary motor area and anterior cingulate cortex relate to compulsive behaviour in healthy controls and individuals with OCD ...
Social Science Research: Principles, Methods and Practices
This book is designed to introduce doctoral and postgraduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioural research, and can serve as a standalone text or as a supplement to research readings in any ...
Social Sciences
Social Sciences is an international, open access journal with rapid peer-review, which publishes works from a wide range of fields, ... In this research, a multi-criteria model (DEX-SOCIAL) was developed to understand the broader aspect of rural sociology and the issue of women's status on the farm. The paper discusses the status of women on ...
Social sciences in crisis: on the proposed elimination of the
The social sciences are facing numerous crises including those related to replication, theory, and applicability. We highlight that these crises imply epistemic malfunctions and affect science communication negatively. Several potential solutions have already been proposed, ranging from statistical improvements to changes in norms of scientific conduct. In this paper, we propose a structural ...
Social sciences
Science and Public Policy Social Forces Social Politics: International Studies in Gender, State & Society Social Problems Social Science Japan Journal Social Work Social Work Research Social Work Research and Abstracts Socio-Economic Review Sociology of Religion. T. Teaching Mathematics and its Applications: An International Journal of the IMA. W
Social Studies of Science: Sage Journals
Since 1970, Social Studies of Science has been a central journal for the field of Science and Technology Studies, serving as a venue for the articulation and development of key ideas and findings in the field from its early years to the current day. The journal is … | View full journal description. This journal is a member of the Committee on ...
Voices from the algorithm: Large language models in social research
Social scientists are often engaged with eliciting the views and opinions of members of the public. Amongst the most prevalent methods are surveys, interviews, and discussion-based formats such as focus groups and deliberative workshops. Digital methods are an approach gaining popularity in the social sciences [1]. Surveys have long taken ...
Understanding Social Science Research: an Overview
Abstract. Social science research is a method to uncover social happenings in human societies. Through social research, new knowled ge is derived to help societies progress and adapt to. change ...
How Pew Research Center will report on generations moving forward
ABOUT PEW RESEARCH CENTER Pew Research Center is a nonpartisan fact tank that informs the public about the issues, attitudes and trends shaping the world. It conducts public opinion polling, demographic research, media content analysis and other empirical social science research. Pew Research Center does not take policy positions.
Social sciences
An ambitious investigation has analysed discourse on eight social-media platforms, covering a vast array of topics and spanning several decades. It reveals that online conversations increase in ...
Shaping the future of behavioral and social research at NIA
Innovating and supporting large-scale observational studies, mechanistic investigations, and translational research to better understand how social and behavioral factors shape biological aging, well-being, and health. We hope you will stay informed about NIA's BSR-focused research and join us on that journey by signing up for the BSR newsletter.
Transformative Research Methods to Increase Social Impact for
An example of political pressure that drives researchers to demonstrate impact arose when the European Commission (EU) (2013) questioned the usefulness of social science and humanities research because the impact of the research for improved social conditions was not systematically documented. In response to this challenge, the EU funded the IMPACT-EV initiative that was led by a team of ...
Infected: Understanding the spread of behavior
Nature Human Behaviour, 2024; DOI: 10.1038/s41562-024-01865-. University of Pittsburgh. "Infected: Understanding the spread of behavior." ScienceDaily. ScienceDaily, 23 April 2024. <www ...
Research articles
Read the latest Research articles from Humanities and Social Sciences Communications. ... Research articles. Filter By: Article Type. All. All; Article (2795) Year. All. All; 2024 (464) 2023 (899)
The Journal of Social Studies Research: Sage Journals
The Journal of Social Studies Research (JSSR) is an internationally recognized peer-reviewed journal designed to foster the dissemination of scholarly ideas and empirical research findings related to k-16 social studies education. The purpose of the journal is to share new knowledge and innovative ideas that contribute to the improvement of social studies education across the world.
In the brain, bursts of beta rhythms implement cognitive control
Beta bursts, they argue, quickly establish flexible but controlled patterns of neural activity for implementing intentional thought. "Cognition depends on organizing goal-directed thought, so if you want to understand cognition, you have to understand that organization," said co-author Earl K. Miller, Picower Professor in The Picower ...
Latest science news, discoveries and analysis
Latest science news and analysis from the world's leading research journal. ... Genetic pedigrees spanning nine generations uncover the social organization of a nomadic empire that dominated much ...