Analyzing Inequalities: An Introduction to Race, Class, Gender, and Sexuality Using the General Social Survey


Catherine E. Harnois

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    This book seeks to provide students and faculty with a resource for connecting sociological issues with real-world data analysis in the context of introductory-level courses. It is not meant to be a comprehensive guide to social statistics, nor is it meant to provide statistical findings concerning every single issue related to inequality—clearly an impossible task! Rather, the goal is to provide readers with (1) an introduction to secondary data analysis in the social sciences, (2) an overview of the range of questions included in the General Social Survey (GSS) that are related to social inequalities, and (3) some basic techniques for analyzing this data online. Though the analytic techniques covered are basic, it is hoped that through active engagement with online data analysis, readers will gain a better understanding of social science research and will be better positioned to ask and answer the questions that are of most interest them.

    The first two chapters provide students with an introduction to social science survey research and an overview of data-related concepts. Chapter 1 addresses the importance of survey research for issues related to social inequality and the benefits and limitations of using survey research to address social inequalities. It outlines four key themes in social justice statistics: power and inequality, socially constructed differences, links between the individual and the broader society, and intersecting inequalities. These themes are carried through the remainder of the book. Chapter 2 introduces students to the GSS and SDA (the Computer-Assisted Survey Methods Program’s Survey Documentation and Analysis website) as well as basic concepts in data analysis, including level of measurement and measures of central tendency. While this is a lot of information to be covered in a single chapter, these concepts are then reinforced throughout the remaining chapters. In this book, unlike traditional statistics textbooks, students do not need to master all the concepts presented in Chapter 2 before proceeding to subsequent chapters. Rather, the book is designed in such a way that readers master these concepts as they progress through the subsequent chapters.

    Chapters 3 through 6 focus on gender, race and ethnicity, class, and sexuality. Because this book is meant to be used alongside a more substantive introductory text, Chapters 3 through 6 are designed to be read in any order. It is expected that an instructor might assign only two or three of these chapters and pair them with more qualitative or theoretical readings. Thus, in Analyzing Inequalities, in contrast to traditional social science statistics books, the statistical concepts and techniques do not build on each other from chapter to chapter. Instead, the basic tools of data analysis (e.g., finding variables, producing and interpreting univariate descriptive statistics, crosstabs, creating charts and graphs, selecting cases) are reinforced in each chapter. Taken together, these chapters provide students multiple opportunities to practice basic data analysis using a variety of variables and to investigate a wide range of issues related to social inequality.

    While Chapters 3 through 6 focus primarily on individual systems of inequality, Chapters 7 through 9 take a more intersectional approach, highlighting the interplay of multiple systems of inequality within social institutions. Chapter 7 focuses on family, Chapter 8 on education, and Chapter 9 on work. The analyses presented in these chapters are exploratory, and the goal is to provide neither a comprehensive overview of these topics nor the “final word” on any of the research questions presented. It is my hope that readers will see limitations in all the analyses and exercises presented here, and that this will then entice some to examine these issues with greater theoretical and methodological complexity.

    Instructors, sign in at for the following instructor resources:

    • Answers to end of chapter multiple choice questions;
    • Guided answers for in-text essay questions; and
    • Bonus multiple choice test bank questions for each chapter.


    Writing this book has taken several years and would not have been possible without a supportive network of colleagues, friends, and family. At Wake Forest University, I have benefited from working with a number of generous colleagues. I am grateful to Joseph Soares, Ana Wahl, Catherine Ross, and Saylor Breckenridge, each of whom gave me valuable feedback. I am particularly indebted to Steve Gunkel, who reviewed the entire manuscript—several chapters twice!—with a fine-tooth comb, and whose insights and attention to detail have improved literally every page of the book. It is difficult for me to imagine a more generous friend and colleague.

    Over the duration of this project, I had the good fortune of working with three undergraduate research assistants: Sydni Williams, Ann Nguyen, and Ashley Mitchell. In addition to providing me with feedback about the book, they have helped me to think through issues of education, family, and intellectual activism.

    In the process of writing this book, I participated in a panel on intersectional pedagogy at the 2015 annual meeting of the Southern Sociological Society. The comments and discussion that this panel generated were both insightful and motivating, and I am grateful to the organizers of this panel, Marni Brown and Cameron Lippard, for creating a place for this dialogue. In addition, this book has benefited from the insights of João Luiz Bastos, who has taught me much and has helped me to think more clearly about intersectionality, social statistics, and the relationship between the two.

    Jeff Lasser at Sage has guided me through the publication process, and it has been a wonderful experience to work with and learn from him. I am also grateful to the individual reviewers who took the time to carefully read and evaluate the book proposal and manuscript. In particular, I would like to thank Robert S. Bausch, Cameron University; Jennifer Roebuck Bulanda, Miami University; Fareeda Griffith, Denison University; Peter Meiksins, Cleveland State University; Kerry Strand, Hood College; Esther Isabelle Wilder, Lehman College and The Graduate Center, The City University of New York (CUNY); Cari Beecham-Bautista, College of DuPage; Jason Lee Crockett, Kutztown University of Pennsylvania; Geoff Harkness, Morningside College; Lorien Lake-Corral, University of Maine at Augusta; William A. Mirola, Marian University; Julia Nevarez, Kean University; Thomas Piñeros Shields, University of Massachusetts Lowell; and Maura Ryan, Georgia State University. Their feedback has been invaluable.

    In this and other projects, I am deeply indebted to Robin W. Simon, Barbara Risman, and Brian Powell for their continued mentorship and support. I am especially grateful to Joe Harrington, who has provided me with a constant stream of encouragement and patience for the past decade and who has, among other things, helped me to see the beauty of short, clear sentences (unlike this one). To the extent that they appear here, credit is his. My thanks also go to Toni and Tom Merfeld, Charlie Harrington, Jo Cox, Sandya Hewamanne, Neil DeVotta, Kim Babon, and Mark Ashley and my parents, Jim and Sheila, all of whom have helped me to see this project from start to finish.

    Finally, my deep appreciation goes to the Computer-Assisted Survey Methods Program (CSM), which develops and maintains the outstanding Survey Documentation and Analysis (SDA) package. CSM was originally part of the University of California, Berkeley, and is now part of the Institute for Scientific Analysis. I thank the individuals and institutions responsible for creating the General Social Survey (GSS) and for maintaining and enhancing it for nearly 50 years. The GSS is a project of the independent research organization NORC at the University of Chicago, with principal funding from the National Science Foundation. At the time of this writing, more than 25,000 scholarly articles, chapters, books, and presentations have used data from the GSS to advance knowledge about American society—44 years of extremely high-quality survey data pertaining to a range of inequalities and available for free to students, researchers, and anyone else who may be interested. This is something from which we can all benefit and for which we might all be grateful.

  • About the Author

    Catherine E. Harnois is Associate Professor in the Departments of Sociology and Women’s, Gender, and Sexuality Studies at Wake Forest University, where she teaches courses on social inequality and research methods. Her work on the intersection of gender and racial discrimination received the 2012 Outstanding Contribution toScholarship Article Award from the American Sociological Association Section on Race, Gender, and Class. Her research has appeared in the journals Gender & Society, Ethnic and Racial Studies, Sociological Forum, Social Psychology Quarterly, Sociology of Race and Ethnicity, and the National Women’s Studies Association Journal, in addition to other scholarly outlets.

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