The Practice of Social Research (12th Edition)

The Practice of Social Research

A Note from the Author

riting is my joy, sociology my passion. I delight in putting words together in a way that makes people learn or laugh or both. Sociology shows up as a set of words, also. It represents our last, best hope for planet-training our race and ﬁnding ways for us to live together. I feel a special excitement at being present when sociology, at last, comes into focus as an idea whose time has come. I grew up in small-town Vermont and New Hampshire. When I announced I wanted to be an auto-body mechanic, like my dad, my teacher told me I should go to college instead. When Malcolm X announced he wanted to be a lawyer, his teacher told him a colored boy should be something more like a carpenter. The difference in our experiences says something powerful about the idea of a level playing ﬁeld. The inequalities among ethnic groups run deep. I ventured into the outer world by way of Harvard, the USMC, U.C. Berkeley, and twelve years teaching at the University of Hawaii. I resigned from teaching in 1980 and wrote full-time for seven years, until the call of the classroom

became too loud to ignore. For me, teaching is like playing jazz. Even if you perform the same number over and over, it never comes out the same twice and you don’t know exactly what it’ll sound like until you hear it. Teaching is like writing with your voice. At last, I have matured enough to rediscover and appreciate my roots in Vermont each summer. Rather than a return to the past, it feels more like the next turn in a widening spiral. I can’t wait to see what’s around the next bend.

TWELFTH EDITION

The Practice of Social Research Earl Babbie Chapman University

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The Practice of Social Research, Twelfth Edition Earl Babbie Acquisitions Editor: Chris Caldeira Development Editor: Dan Moneypenny Assistant Editor: Rachael Krapf Editorial Assistant: Rebecca Boorsma Technology Project Manager: Lauren Keyes

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Dedication Suzanne Babbie

Contents in Brief

PA RT 1

An Introduction to Inquiry 1 1 Human Inquiry and Science 2 2 Paradigms, Theory, and Social Research 31 3 The Ethics and Politics of Social Research 62 PA RT 2

The Structuring of Inquiry: Quantitative and Qualitative 89 4 Research Design 90 5 Conceptualization, Operationalization, and Measurement 124 6 Indexes, Scales, and Typologies 160 7 The Logic of Sampling 187 PA RT 3

Modes of Observation: Quantitative and Qualitative 229 8 Experiments 230 9 Survey Research 253 10 Qualitative Field Research 295

11 Unobtrusive Research 331 12 Evaluation Research 362 PA RT 4

Analysis of Data: Quantitative and Qualitative 391 13 14 15 16 17

Qualitative Data Analysis 393 Quantitative Data Analysis 421 The Elaboration Model 448 Statistical Analyses 466 Reading and Writing Social Research 505

Appendixes A1 A B C D E F G

Using the Library A2 GSS Household Enumeration Questionnaire A12 Random Numbers A22 Distribution of Chi Square A24 Normal Curve Areas A26 Estimated Sampling Error A27 Twenty Questions a Journalist Should Ask about Poll Results A28

Contents in Detail

Preface xiv Acknowledgments xxiii

Part 1

An Introduction to Inquiry 1

CHAPTER 1

Human Inquiry and Science 2 Introduction 3 Looking for Reality 4 Knowledge from Agreement Reality 4 Errors in Inquiry, and Some Solutions 6 What’s Really Real? 8

The Foundations of Social Science 10 Theory, Not Philosophy or Belief 11 Social Regularities 11 Aggregates, Not Individuals 13 Concepts and Variables 14

The Purposes of Social Research 19 The Ethics of Human Inquiry 19 Some Dialectics of Social Research 19 Idiographic and Nomothetic Explanation 20 Inductive and Deductive Theory 21 Qualitative and Quantitative Data 23 Pure and Applied Research 25

The Research Proposal 27

CHAPTER 2

Paradigms, Theory, and Social Research 31 Introduction 32 Some Social Science Paradigms 32 Macrotheory and Microtheory 34 Early Positivism 34 Social Darwinism 35 Conﬂict Paradigm 36 Symbolic Interactionism 36 Ethnomethodology 37 Structural Functionalism 38 Feminist Paradigms 39 Critical Race Theory 40 Rational Objectivity Reconsidered 41

Elements of Social Theory 44 Two Logical Systems Revisited 46 The Traditional Model of Science 46 Deductive and Inductive Reasoning: A Case Illustration 48 A Graphic Contrast 51

Deductive Theory Construction 53 Getting Started 53 Constructing Your Theory 54 An Example of Deductive Theory: Distributive Justice 54

Inductive Theory Construction 56 An Example of Inductive Theory: Why Do People Smoke Marijuana? 57 vii

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The Links between Theory and Research 58 Research Ethics and Theory 59

Nomothetic Causal Analysis and HypothesisTesting 96 False Criteria for Nomothetic Causality 96

Necessary and Sufﬁcient Causes 97 Units of Analysis 98 CHAPTER 3

The Ethics and Politics of Social Research 62 Introduction 63 Ethical Issues in Social Research 64 Voluntary Participation 64 No Harm to the Participants 65 Anonymity and Conﬁdentiality 67 Deception 70 Analysis and Reporting 71 Institutional Review Boards 72 Professional Codes of Ethics 75

Two Ethical Controversies 75 Trouble in the Tearoom 75 Observing Human Obedience 76

The Politics of Social Research 77 Objectivity and Ideology 78 Politics with a Little “p” 81 Politics in Perspective 82

Part 2

The Structuring of Inquiry: Quantitative and Qualitative 89

Individuals 100 Groups 100 Organizations 101 Social Interactions 101 Social Artifacts 103 Units of Analysis in Review 103 Faulty Reasoning about Units of Analysis: The Ecological Fallacy and Reductionism 104

The Time Dimension 106 Cross-Sectional Studies 106 Longitudinal Studies 107 Approximating Longitudinal Studies 110 Examples of Research Strategies 112

How to Design a Research Project 112 Getting Started 113 Conceptualization 115 Choice of Research Method 115 Operationalization 116 Population and Sampling 116 Observations 116 Data Processing 117 Analysis 117 Application 117 Research Design in Review 117

The Research Proposal 119 Elements of a Research Proposal 119

The Ethics of Research Design 120 CHAPTER 4

Research Design 90 Introduction 91 Three Purposes of Research 92 Exploration 92 Description 93 Explanation 94

The Logic of Nomothetic Explanation 94 Criteria for Nomothetic Causality 94

CHAPTER 5

Conceptualization, Operationalization, and Measurement 124 Introduction 125 Measuring Anything That Exists 125

Contents

Conceptions, Concepts, and Reality 126 Concepts as Constructs 128

Conceptualization 130 Indicators and Dimensions 131 The Interchangeability of Indicators 133 Real, Nominal, and Operational Deﬁnitions 134 Creating Conceptual Order 134 An Example of Conceptualization: The Concept of Anomie 136

Deﬁnitions in Descriptive and Explanatory Studies 138 Operationalization Choices 139 Range of Variation 140 Variations between the Extremes 141 A Note on Dimensions 142 Deﬁning Variables and Attributes 142 Levels of Measurement 143 Single or Multiple Indicators 147 Some Illustrations of Operationalization Choices 148 Operationalization Goes On and On 149

Criteria of Measurement Quality 150 Precision and Accuracy 150 Reliability 150 Validity 153 Who Decides What’s Valid? 155 Tension between Reliability and Validity 156

The Ethics of Measurement 156

CHAPTER 6

Indexes, Scales, and Typologies 160 Introduction 161 Indexes versus Scales 161 Index Construction164 Item Selection 164 Examination of Empirical Relationships 165 Index Scoring 170

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Handling Missing Data 171 Index Validation 173 The Status of Women: An Illustration of Index Construction 176

Scale Construction 177 Bogardus Social Distance Scale 177 Thurstone Scales 178 Likert Scaling 179 Semantic Differential 180 Guttman Scaling 181

Typologies 183 CHAPTER 7

The Logic of Sampling 187 Introduction 188 A Brief History of Sampling 189 President Alf Landon 189 President Thomas E. Dewey 190 Two Types of Sampling Methods 191

Nonprobability Sampling 192 Reliance on Available Subjects 192 Purposive or Judgmental Sampling 193 Snowball Sampling 193 Quota Sampling 194 Selecting Informants 195

The Theory and Logic of Probability Sampling 196 Conscious and Unconscious Sampling Bias 196 Representativeness and Probability of Selection 198 Random Selection 199 Probability Theory, Sampling Distributions, and Estimates of Sampling Error 200

Populations and Sampling Frames 208 Review of Populations and Sampling Frames 210

Types of Sampling Designs 211 Simple Random Sampling 211 Systematic Sampling 211 Stratiﬁed Sampling 214

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Contents

Implicit Stratiﬁcation in Systematic Sampling 216 Illustration: Sampling University Students 217

Strengths and Weaknesses of the Experimental Method 249 Ethics and Experiments 250

Multistage Cluster Sampling 218 Multistage Designs and Sampling Error 218 Stratiﬁcation in Multistage Cluster Sampling 220 Probability Proportionate to Size (PPS) Sampling 221 Disproportionate Sampling and Weighting 222

Probability Sampling in Review 224 The Ethics of Sampling 225

Part 3

Modes of Observation: Quantitative and Qualitative 229

CHAPTER 8

Experiments 230 Introduction 231 Topics Appropriate for Experiments 231 The Classical Experiment 232 Independent and Dependent Variables 232 Pretesting and Posttesting 232 Experimental and Control Groups 233 The Double-Blind Experiment 234

Selecting Subjects 235 Probability Sampling 236 Randomization 236 Matching 236 Matching or Randomization? 237

Variations on Experimental Design 238 Preexperimental Research Designs 238 Validity Issues in Experimental Research 240

An Illustration of Experimentation 244 Alternative Experimental Settings 247 Web-Based Experiments 247 “Natural” Experiments 247

CHAPTER 9

Survey Research 253 Introduction 254 Topics Appropriate for Survey Research 254 Guidelines for Asking Questions 255 Choose Appropriate Question Forms 256 Make Items Clear 257 Avoid Double-Barreled Questions 257 Respondents Must Be Competent to Answer 258 Respondents Must Be Willing to Answer 259 Questions Should Be Relevant 259 Short Items Are Best 260 Avoid Negative Items 260 Avoid Biased Items and Terms 260

Questionnaire Construction 262 General Questionnaire Format 262 Formats for Respondents 262 Contingency Questions 263 Matrix Questions 264 Ordering Items in a Questionnaire 265 Questionnaire Instructions 266 Pretesting the Questionnaire 267 A Composite Illustration 267

Self-Administered Questionnaires 267 Mail Distribution and Return 270 Monitoring Returns 271 Follow-up Mailings 272 Response Rates 272 A Case Study 273

Interview Surveys 274 The Role of the Survey Interviewer 274 General Guidelines for Survey Interviewing 275 Coordination and Control 278

Contents

Telephone Surveys 279 Computer-Assisted Telephone Interviewing (CATI) 281 Response Rates in Interview Surveys 282

Online Surveys 283 Comparison of the Different Survey Methods 285 Strengths and Weaknesses of Survey Research 287 Secondary Analysis 288

Ethics and Survey Research 292

CHAPTER 10

Qualitative Field Research 295 Introduction 296 Topics Appropriate for Field Research 296 Special Considerations in Qualitative Field Research 299 The Various Roles of the Observer 299 Relations to Subjects 301

Some Qualitative Field Research Paradigms 303 Naturalism 303 Ethnomethodology 306 Grounded Theory 307 Case Studies and the Extended Case Method 309 Institutional Ethnography 311 Participatory Action Research 313

Conducting Qualitative Field Research 316 Preparing for the Field 316 Qualitative Interviewing 318 Focus Groups 322 Recording Observations 324

Strengths and Weaknesses of Qualitative Field Research 326 Validity 327 Reliability 328

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Ethics and Qualitative Field Research 328

CHAPTER 11

Unobtrusive Research 331 Introduction 332 Content Analysis 333 Topics Appropriate for Content Analysis 333 Sampling in Content Analysis 334 Coding in Content Analysis 338 Illustrations of Content Analysis 342 Strengths and Weaknesses of Content Analysis 344

Analyzing Existing Statistics 344 Durkheim’s Study of Suicide 345 The Consequences of Globalization 346 Units of Analysis 347 Problems of Validity 347 Problems of Reliability 348 Sources of Existing Statistics 349

Comparative and Historical Research 350 Examples of Comparative and Historical Research 351 Sources of Comparative and Historical Data 355 Analytic Techniques 357

Ethics and Unobtrusive Measures 259

CHAPTER 12

Evaluation Research 362 Introduction 363 Topics Appropriate for Evaluation Research 364 Formulating the Problem: Issues of Measurement 366 Specifying Outcomes 367 Measuring Experimental Contexts 368

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Specifying Interventions 368 Specifying the Population 369 New versus Existing Measures 369 Operationalizing Success/Failure 369

Types of Evaluation Research Designs 370 Experimental Designs 370 Quasi-Experimental Designs 371 Qualitative Evaluations 375

The Social Context 377 Logistical Problems 377 Use of Research Results 379

Social Indicators Research 384 The Death Penalty and Deterrence 384 Computer Simulation 385

Ethics and Evaluation Research 386

Part 4

Analysis of Data: Quantitative and Qualitative 391

CHAPTER 13

Qualitative Data Analysis 393 Introduction 394 Linking Theory and Analysis 394 Discovering Patterns 394 Grounded Theory Method 396 Semiotics 397 Conversation Analysis 399

Qualitative Data Processing 400 Coding 400 Memoing 404 Concept Mapping 405

Computer Programs for Qualitative Data 406 QDA Programs 406 Leviticus as Seen through NUD*IST 407 Using NVivo to Understand Women Film Directors, by Sandrine Zerbib 411

The Qualitative Analysis of Quantitative Data 413 Evaluating the Quality of Qualitative Research 414 Ethics and Qualitative Data Analysis 418

CHAPTER 14

Quantitative Data Analysis 421 Introduction 422 Quantiﬁcation of Data 422 Developing Code Categories 423 Codebook Construction 425 Data Entry 426

Univariate Analysis 426 Distributions 427 Central Tendency 428 Dispersion 431 Continuous and Discrete Variables 432 Detail versus Manageability 433

Subgroup Comparisons 433 “Collapsing” Response Categories 434 Handling “Don’t Knows” 435 Numerical Descriptions in Qualitative Research 436

Bivariate Analysis 436 Percentaging a Table 438 Constructing and Reading Bivariate Tables 440

Introduction to Multivariate Analysis 441 Sociological Diagnostics 442 Ethics and Quantitative Data Analysis 444

CHAPTER 15

The Elaboration Model 448 Introduction 449 The Origins of the Elaboration Model 449

Contents

The Elaboration Paradigm 454 Replication 455 Explanation 455 Interpretation 457 Speciﬁcation 457 Reﬁnements to the Paradigm 460

Elaboration and Ex Post Facto Hypothesizing 462

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Organizing a Review of the Literature 506 Reading Journals versus Books 507 Evaluating Research Reports 508

Using the Internet Wisely 513 Some Useful Websites 513 Searching the Web 514 Evaluating the Quality of Internet Materials 518 Citing Internet Materials 520

Writing Social Research 521 CHAPTER 16

Statistical Analyses 466 Introduction 467 Descriptive Statistics 467 Data Reduction 467 Measures of Association 468 Regression Analysis 472

Inferential Statistics 476 Univariate Inferences 476 Tests of Statistical Signiﬁcance 478 The Logic of Statistical Signiﬁcance 479 Chi Square 483 t-Test 485 Some Words of Caution 486

Other Multivariate Techniques 488 Path Analysis 488 Time-Series Analysis 489 Factor Analysis 491 Analysis of Variance 493 Discriminant Analysis 495 Log-Linear Models 498 Geographic Information Systems (GIS) 500

CHAPTER 17

Reading and Writing Social Research 505 Introduction 506 Reading Social Research 506

Some Basic Considerations 521 Organization of the Report 523 Guidelines for Reporting Analyses 526 Going Public 527

The Ethics of Reading and Writing Social Research 528

Appendixes A1 A Using the Library A2 B GSS Household Enumeration Questionnaire A12 C Random Numbers A22 D Distribution of Chi Square A24 E Normal Curve Areas A26 F Estimated Sampling Error A27 G Twenty Questions a Journalist Should Ask about Poll Results A28

Glossary G1 Bibliography B1 Index I1 Photo Credits I10

Preface

A “few” years ago (I hate to tell you how many), I began teaching my ﬁrst course in social research methods. The course focused speciﬁcally on survey research methods, and I had only six students in the class. As the semester progressed, I became more relaxed as a teacher. Before long, my students and I began meeting in my ofﬁce, where I could grab and lend books from my own library as their relevance occurred to me during class meetings. One nagging problem I faced then was the lack of a good textbook on survey research. The available books fell into one of two groups. Some books presented the theoretical logic of research methods in such abstract terms that I didn’t think students would be able to apply any of the general principles to the practical world of “doing” research. The other books were just the opposite. Often termed “cookbooks,” they presented detailed, step-by-step instructions on how to conduct a survey. Unfortunately, this approach only prepared students to conduct surveys very much like the one described by the authors. Neither the abstract nor the “cookbook” approach seemed truly useful to students or their instructors. One day I found myself jotting down the table of contents for my ideal research methods textbook. It was organized around three theoretical principles on which scientiﬁc research is based: 1. Understanding the theoretical principles on which scientiﬁc research is based. 2. Seeing how those principles are reﬂected in the established techniques for doing research. 3. Being prepared to make appropriate compromises whenever ﬁeld conditions do not xiv

permit the routine application of established techniques. The next day, unexpectedly, Wadsworth called and asked me to write a methods text! Survey Research Methods was published in 1973. My editors and I immediately received some good news, some bad news, and some additional good news. The ﬁrst good news was that all survey research instructors seemed to love the book, and it was being used in virtually every survey research course in the country. The bad news was that there weren’t all that many survey research courses. The ﬁnal good news, however, was that many instructors who taught general social research courses—covering survey research alongside other research methods—were inclined to use our book and supplement it with other books dealing with ﬁeld research, experiments, and so on. While adjusting to our specialized book, however, many instructors suggested that Wadsworth have “that same guy” write a more general social research text. The preface of the ﬁrst edition of The Practice of Social Research (1975) acknowledged the assistance of a dozen social research instructors from California to Florida. The book was a collaboration in a very real sense, even though only my name was on the cover and I was ultimately responsible for it. The Practice of Social Research was an immediate success. Although it was initially written for sociology courses, subsequent editions have been increasingly used in ﬁelds such as psychology, public administration, urban studies, education, communications, social sciences, and political

Preface science—in some 30 different disciplines, I’m told. Moreover, it’s being used by teachers and researchers in numerous countries around the world, and in 2000 a Beijing publisher released a two-volume Chinese edition. I’ve laid out this lengthy history of the book for a couple of reasons. First, when I was a student, I suppose I thought of textbooks the same way that I thought about government buildings: They were just there. I never really thought about them as being written by human beings. I certainly never thought about textbooks as evolving: being updated, getting better, having errors corrected. As a student, I would have been horriﬁed by the thought that any of my textbooks might contain mistakes! Second, pointing out the evolution of the book sets the stage for a preview of the changes that have gone into this 12th edition. As with previous revisions, several factors have prompted changes. For example, because social research technology and practices are continually changing, the book must be updated to remain current and useful. In my own teaching, I frequently ﬁnd improved ways to present standard materials. Colleagues also often share their ideas for ways to teach speciﬁc topics. Some of these appear as boxed inserts in the book. Both students and instructors often suggest that various topics be reorganized, expanded, clariﬁed, shrunk, or—gasp—deleted.

New to the 12th Edition In an earlier edition of this book, I said, “Revising a textbook such as this is a humbling experience. No matter how good it seems to be, there is no end of ideas about how it could be improved.” That observation still holds true. When we asked instructors what could be improved, they once again thought of things, and I’ve considered all their suggestions, followed many of them, and chosen to “think some more” about others. I’ve also received numerous comments and suggestions from students who have been assigned the book; many of the changes come from them.

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This edition of the book contains some new features, all of which were suggested by faculty reviewers and users. Research Ethics: In 1973, Survey Research Methods contained an appendix on research ethics, which was one of the few things reviewers criticized: They were against it. Regarding the section “The Rights of Subjects,” one reviewer angrily wrote, “What about the rights of science?” Over the years, concern for research ethics has steadily increased among social researchers, and the topic has become steadily more prominent in the various editions of this book. In the 12th edition, most chapters end with a section examining the ethical implications of the chapter’s topics. Research Proposal: Many instructors now use the research proposal as a vehicle for training students in social research, and several of the reviewers asked for more attention to that topic. As a consequence, each chapter concludes with a continuing exercise inviting students to apply what they’ve learned in the chapter to an evolving research proposal. Keeping Humanity in Focus: Sometimes, social research requires us to delve deeply into the relationships among variables and/or take apart intricate social structures. This leads some researchers and research consumers to worry that we might lose sight of the human beings who lie at the core of our concerns. Some social research efforts, however, undertake sophisticated analyses while keeping an immediate focus on the people involved. A new series of boxes in this edition highlights some of those studies, as follows: Chapter 1: Kathryn Edin and Maria Kefalas, Promises I Can Keep: Why Poor Women Put Motherhood before Marriage (Berkeley: University of California Press, 2005). Chapter 5: Elijah Anderson, A Place on the Corner: A Study of Black Street Corner Men (Chicago: University of Chicago Press, 2004).

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Chapter 10: Rachel Sherman, Class Acts: Service and Inequality in Luxury Hotels (Berkeley: University of California Press, 2005). Chapter 14: Kristen Schilt, “Just One of the Guys? How Transmen Make Gender Visible in the Workplace,” Gender and Society 20, no. 4 (2006): 465–90. Chapter 17: Sudhir Venkatesh, Gang Leader for a Day: A Rogue Sociologist Takes to the Streets (New York: Penguin, 2008). How to Do It: Another new series of boxes in the book provides practical, step-by-step guidance to assist students in dealing with what instructors have identiﬁed as especially elusive tasks. These are the boxes in the series, some of which adapted materials already existing in the book:

• • • • • • •

Chapter 2: Framing a Hypothesis Chapter 4: Identifying the Unit of Analysis Chapter 7: Using a Table of Random Numbers Chapter 9: Conducting an Online Survey Chapter 10: Establishing Rapport Chapter 17: Using Google Scholar Chapter 17: Citing Bibliographic Sources

In addition to these identiﬁable features, I have continued to pursue my intention to demonstrate social research as an international, not just American, undertaking. Since researchers in different parts of the world sometimes face unique problems, the ways in which they deal with those problems often reveal new dimensions to the logic of social inquiry. Here are some of the other changes in this edition, arranged by chapter: Chapter 1, “Human Inquiry and Science” • Provided new section on the purposes of social research

• •

Clariﬁed the top portion of Figure 1-4 Cited evaluation research as a special kind of applied research, to be examined in Chapter 12

Chapter 2, “Paradigms, Theory, and Social Research” • Added discussion of feminist standpoint theory

• • • •

Added discussion of critical realism Introduced the term mesotheory Dropped references to control variables as “test” variables Reviewed concepts of idiographic and nomothetic in “Elements of Social Theory”

Chapter 3, “The Ethics and Politics of Social Research” • Included discussion of the “politicization of science”

•

Added a comment on the positive results of the Tearoom Trade research

•

Added discussion of Zimbardo’s Stanford prison experiment

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Provided new discussion of DHHS “Certiﬁcate of Conﬁdentiality”

• •

Mentioned Nuremberg trials Discussed Tuskegee syphilis experiments

Chapter 4, “Research Design” • Provided example of using cohorts to infer process over time

•

Included a new diagram to illustrate a cohort study

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Provided new section: “Nomothetic Causal Analysis and Hypothesis Testing”

•

Changed Figure 4-5 in previous edition to 4-6 in current

Chapter 5, “Conceptualization, Operationalization, and Measurement” • Gave new opening example of college satisfaction

•

Added materials on using both qualitative and quantitative approaches

•

Clariﬁed the original meaning of “the exception that proves the rule”

•

Included glossary deﬁnitions of epistemology and methodology

•

Discussed many names for snow to illustrate concepts and conceptualization

•

Coordinated deﬁnitions of theory in text and in glossary deﬁnition

•

Provided “fear of crime” example to illustrate dimensions

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•

Included a new box: “Measuring College Satisfaction”

•

Added reference to registration-based sampling (RBS)

•

Discussed the Geertz concept of “thick description”

•

Referenced discussion of random-digit dialing and problems of cell phones in Chapter 9

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Gave a new summary table reviewing direct and indirect observables and constructs

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Added a paragraph illustrating the importance of keeping the operationalization process open

Chapter 8, “Experiments” • Explained why experiments are discussed ﬁrst

• • •

Clariﬁed the deﬁnition of validity

•

Discussed differences in qualitative and quantitative conceptualization and operationalization

Added a paragraph distinguishing sex and gender Changed the diagram of the conceptualization process to a table with examples

Chapter 6, “Indexes, Scales, and Typologies” • Discussed how indicators of a variable may be unrelated to one another

• •

Introduced the term ﬁeld experiment Mentioned why we might use preexperimental methods

Chapter 9, “Survey Research” • Updated and expanded section on online survey research

• • •

Included box on using Survey Monkey Expanded description of random-digit dialing Expanded discussion of problems created by cell phones

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Referenced cognitive interviewing regarding pretesting questionnaires

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Reported that interviewer behavior changes over the course of a survey project

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Used Obama-Clinton primary as example for social desirability

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Chapter 7, “The Logic of Sampling” • Mentioned that standard error can be calculated for means and other measures

Noted suggestion that interviewers might be given more latitude in correcting respondent errors

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Discussed the use of PDAs for survey interviewing or self-administered surveys

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Discussed the problems of bias that cell phones create for telephone survey sampling

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Expanded and updated the discussion of response rates

• •

Revised the glossary deﬁnition of sampling error

•

Discussed the decline in interview survey response rates

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Added discussion of “Webometrics Ranking” of universities to the box on U.S. News ranking

• •

Expanded the captions for Figures 6-2 and 6-3 Provided new box on “Indexing the World” showing a variety of indexes rating various aspects of life

Gave new example of snowball sampling: using social networks of nonheterosexual women in small-town U.K.

•

Corrected the discussion of the ﬁnite population correction

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Worked in the quip: “Statistics means never having to say you are certain.”

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Expanded discussion of cell-phone-only population

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Added a discussion of “theoretical sampling” in qualitative research projects

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Discussed recent address-based sampling (ABS)

Chapter 10, “Qualitative Field Research” • Updated Loﬂand references with new, greatly revised version

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Gave example of using Internet for qualitative interviewing

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Discussed researcher responsibilities in participatory action research

• •

Discussed and deﬁned emancipatory research Provided box on giving pencils and cameras to Peruvian Indians in rainforest

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Mentioned study of globalization impact among Irish young people that used drawings, poems, and songs

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Discussed study combining focus groups and in-depth interviews in Sweden

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Added pictures of some leading qualitative ﬁeld researchers

• • •

Updated discussion of focus groups Introduced the “ethnographic fallacy” Added example of Jeffrey Kidder’s study of bike messengers in New York City

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Used Peter Rossi et al. deﬁnition of evaluation research

Chapter 13, “Qualitative Data Analysis” • Provided major new section on the evaluation of qualitative research

• •

Included new section on QDA programs Updated Loﬂand to newest edition

Chapter 14, “Quantitative Data Analysis” • Clariﬁed the base for percentaging tables

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Illustrated subgroup comparison with GSS example

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Introduced GapMinder as resource for displaying data

• • •

Provided new discussion on how to read tables

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Introduced Loﬂand’s notion of “selective competence” in subjects and discussed it in terms of rapport

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Discussed how to continue interviewing difﬁcult informants

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Referenced article on the difﬁculty of writing autoethnography

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Described kaupapa Maori research as an example of PAR

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Updated data on example of gender, age, and church attendance

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Mentioned Silent Racism as an example of nonpolitical, nonmarketing focus groups

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Updated data on example of income by education and gender

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Updated the data on example of age and attitude toward marijuana

Chapter 11, “Unobtrusive Research” • Updated Megatrends studies

Updated and clariﬁed discussion of Table 14-12 Updated and clariﬁed the discussion of Table 14-4

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Gave lengthy example of qualitative content analysis of rap music

Chapters 15, “The Elaboration Model”

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Cited the University of Michigan’s archive of data sources

Chapter 16, “Statistical Analyses”

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Discussed and cited census website for mapping data

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Discussed and cited computer programs for qualitative and quantitative content analysis

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Discussed the uses of the Social Explorer for mapping data

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Updated Megatrends studies

Chapter 12, “Evaluation Research” • Discussed the Sabido methodology for social change through mass media

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Gave example of “empowerment evaluation” in connection with Australian school program

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Updated examples of topics appropriate for evaluation research

• •

No signiﬁcant changes made

Added section on t-tests

Chapter 17, “Reading and Writing Social Research”

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Discussed Middlebury College history department banning of citing Wikipedia as a source

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Updated and expanded warnings of misconceptions and biases on the web

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Illustrated common bibliographic citation formats

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Introduced SourceWatch as a resource for judging websites

As always, I’ve updated materials throughout the book. As an instructor, I’m constantly searching for new and more effective ways of explaining social research to my own students; many of those

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new explanations take the form of diagrams. You’ll ﬁnd several new graphic illustrations in this edition. Once again, I’ve sought to replace older research examples (except for the classics) with more recent ones. I’ve also dropped some sections that I don’t think do much for students anymore. As with each new edition, I would appreciate any comments you have about how the book can be improved. Its evolution over the past 35 years has reﬂected countless comments from students and others.

Boxed examples and discussions Students tell me they like the boxed materials that highlight particular ideas and studies, as well as varying the format of the book. Beginning in the tenth edition, I’ve been using boxes that focus on the ways the mass media use and misuse social research.

Pedagogical Features

Main Points At the end of each chapter, a concise list of main points provides both a brief chapter summary and a useful review. The main points let students know exactly what ideas they should focus on in each chapter.

Although students and instructors alike have told me that the past editions of this book were effective tools for learning research methods, I have used this revision as an opportunity to review the book from a pedagogical standpoint, ﬁne-tuning some elements, adding others. Here’s the package we came up with in the 12th edition. Chapter Overview Each chapter is preceded by a pithy focus paragraph that highlights the principal content of the chapter. Chapter Introduction Each chapter opens with an introduction that lays out the main ideas in that chapter and, importantly, relates them to the content of other chapters in the book. Clear and provocative examples Students often tell me that the examples—real and hypothetical—have helped them grasp difﬁcult and/or abstract ideas, and this edition has many new examples as well as those that have proved particularly valuable in earlier editions. Graphics From the ﬁrst time I took a course in research methods, most of the key concepts have made sense to me in graphic form. Whereas my task here has been to translate those mental pictures into words, I’ve also included some graphics in the book. Advances in computer graphics have helped me communicate to the Wadsworth artists what I see in my head and would like to share with students. I’m delighted with the new graphics in this edition.

Running glossary Key terms are highlighted in the text, and deﬁnitions for each term are listed at the bottom of the page. This will help students learn the deﬁnitions of these terms and locate them in each chapter to review them in context.

Key Terms A list of key terms follows the main points. These lists reinforce the students’ acquisition of necessary vocabulary. The new vocabulary in these lists is deﬁned in context in the chapters. The terms are boldfaced in the text, deﬁned in the running glossary that appears at the bottom of the page throughout the text, and included in the glossary at the back of the book. Proposing Social Research This series of linked exercises invites students to apply what they’ve learned in the chapter by treating those topics in an evolving research proposal. Review Questions and Exercises This review aid allows students to test their understanding of the chapter concepts and apply what they’ve learned. SPSS Exercises and Online Study Resources This edition continues previous editions’ movement into cyberspace. Students can use the annotated list of useful websites in this section, as well as other resources mentioned, to take their learning beyond the text and classroom. Appendixes As in previous editions, a set of appendixes provides students with some research tools, such as a guide to the library, a

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table of random numbers, and so forth. There is an SPSS primer on the book’s website along with primers for NVivo and Qualrus. Clear and accessible writing This is perhaps the most important “pedagogical aid” of all. I know that all authors strive to write texts that are clear and accessible, and I take some pride in the fact that this “feature” of the book has been one of its most highly praised attributes through its 11 previous editions. It’s the one thing students write most often about. For the 12th edition, the editors and I have taken special care to reexamine literally every line in the book, pruning, polishing, embellishing, and occasionally restructuring for a maximally “reader-friendly” text. Whether you’re new to this book or intimately familiar with previous editions, I invite you to open any chapter and evaluate the writing for yourself.

Supplements The Practice of Social Research, 12th edition, is accompanied by a wide array of supplements prepared for both the instructor and student to create the best learning environment inside as well as outside the classroom. All the continuing supplements for The Practice of Social Research, 12th edition, have been thoroughly revised and updated. I invite you to examine and take full advantage of the teaching and learning tools available to you.

For the Student Guided Activities for The Practice of Social Research, 12th Edition ISBN-10 049559847X The student study guide and workbook Ted Wagenaar and I have prepared continues to be a mainstay of my own teaching. Students tell me they use it heavily as a review of the text, and I count the exercises as half their grade in the course. In this edition, Ted and I have once again sorted through the exercises and added new ones

we’ve created in our own teaching or heard about from colleagues. These include matching, multiplechoice, and open-ended discussion questions for each chapter, along with four to six exercises that use examples from everyday life to reinforce the material learned in the text. Also included are the answers to the matching and multiple-choice review questions, as well as a General Social Survey appendix, plus chapter objectives, chapter summaries, and key terms.

SPSS Student Version CD-ROM 16.0 (Windows only) ISBN-10 0495598275 Based on the professional version of one of the world’s leading desktop statistical software packages, SPSS Student Version for Windows provides real-world software for students to do sociological data analysis, such as interpreting the GSS data sets found on the companion website.

SPSS Practice Workbook ISBN-10 0495598461 This handy guide is coordinated with the text and SPSS CD-ROM 16.0 to help students learn basic navigation in SPSS, including how to enter their own data; create, save, and retrieve ﬁles; produce and interpret data summaries; and much more. Also included are SPSS practice exercises correlated with each chapter. The guide comes free when bundled with the text.

GSS Data Disk

ISBN-10 0495093297

Over the years, the publisher and I have sought to provide up-to-date personal computer support for students and instructors. Because there are now many excellent programs for analyzing data, we’ve provided data to be used with them. With this edition, we’ve updated the data disk to include the 2006 GSS data.

Experiencing Social Research: An Introduction Using MicroCase, 2nd Edition ISBN-10 0534519113 This supplementary workbook and statistical package, written by David J. Ayers of Grove City

Preface College, includes short discussions, quizzes, and computerized exercises in which students will learn and apply key methodological concepts and skills by analyzing, and in some cases collecting and building, simple data ﬁles for real sociological data. Designed to accompany The Practice of Social Research, the workbook and statistical package take a step-by-step approach to show students how to do real sociological research, using the same data and techniques used by professional researchers, to reinforce, build on, and complement course materials.

Readings in Social Research, 3rd Edition ISBN-10 0495093378 The concepts and methodologies of social research come to life in this interesting collection of articles speciﬁcally designed to accompany The Practice of Social Research. Diane Kholos Wysocki includes an interdisciplinary range of readings from the ﬁelds of psychology, sociology, social work, criminal justice, and political science. The articles focus on the important methods and concepts typically covered in the social research course and provide an illustrative advantage. Organized by key concepts, each of the reader’s ten chapters begins with an introduction highlighting and explaining the research concept that each chapter’s readings elucidate.

For the Instructor Instructor’s Resource Manual with Test Bank ISBN-10 0495598488 This supplement offers the instructor brief chapter outlines, behavioral objectives, ASA recommendations, detailed chapter outlines, teaching suggestions and resources, video suggestions, questions/ activities to guide research projects, scenarios that apply social research to everyday life, InfoTrac® College Edition exercises, and Internet exercises. In addition, for each chapter of the text, the Test Bank has 50–70 multiple-choice questions, 20–25 true-false questions, and 5 essay questions with answers and page references. All questions are

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labeled as new, modiﬁed, or pickup so instructors know if the question is new to this edition of the Test Bank, picked up but modiﬁed from the previous edition of the Test Bank, or picked up straight from the previous edition.

PowerLecture with JoinIn™ and ExamView® CD-ROM ISBN-10 049559850X This easy-to-use, one-stop digital library and presentation tool includes the following:

•

Ready-to-use Microsoft® PowerPoint® lecture slides, making it easy for you to assemble, edit, publish, and present custom lectures for your course

•

Video-based polling and quiz questions that can be used with the JoinIn™ on Turning-Point® personal response system

•

ExamView® testing software, which provides all the test items from the text’s printed test bank in electronic format, enabling you to create customized tests of up to 250 items that can be delivered in print or online

•

The text’s Instructor’s Resource Manual in electronic format

ABC Video—Research Methods, Volume I VHS: ISBN-10 0495804312 DVD: ISBN-10 049580438X This series of videos comprising footage from ABC broadcasts is specially selected and arranged to accompany your research methods course. The segments may be used in conjunction with Wadsworth’s research methods texts to help provide a real-world example to illustrate course concepts or to instigate discussion. These ABC videos feature short, high-interest clips from current news events as well as historic raw footage going back 40 years. Clips are drawn from such programs as World News Tonight, Good Morning America, This Week, PrimeTime Live, 20/20, and Nightline, as well as numerous ABC News specials and material from the Associated Press Television News and British Movietone News collections.

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Internet-Based Supplements CengageNow™ This feature empowers students with the ﬁrst assessment-centered student tutorial system for Social Research/Research Methods. Seamlessly tied to the new edition, this interactive web-based learning tool helps students gauge their unique study needs with a “pretest” for each chapter to assess their understanding of the material. They are then given a personalized study plan that offers interactive, visual, and audio resources to help them master the material. They can check their progress with an interactive posttest as well.

WebTutor™ on Blackboard® and WebCT® This web-based software for students and instructors takes a course beyond the classroom to an anywhere, anytime environment. Students gain access to the rich content from this book’s companion websites. Available for WebCT and Blackboard only.

InfoTrac® College Edition with InfoMarks™ Available as a free option with newly purchased texts, InfoTrac College Edition gives instructors and students four months of free access to an extensive online database of reliable, full-length articles (not just abstracts) from thousands of scholarly and popular publications going back as far as 22 years. Among the journals available are American Journal of Sociology, Social Forces, Social Research, and Sociology. InfoTrac College Edition now also comes with InfoMarks, a tool that allows you to save your search parameters, as well as save links to speciﬁc articles. (Available to North American college and university students only; journals are subject to change.)

Companion Website for The Practice of Social Research, 12th Edition The book’s companion website (www.cengage .com/sociology/babbie) includes chapter-speciﬁc resources for instructors and students. For instructors, the site offers a password-protected instructor’s manual, Microsoft PowerPoint presentation slides, and more. For students, there is a multitude of text-speciﬁc study aids, including the following:

• • • • • •

Tutorial practice quizzing Web links InfoTrac College Edition key terms Flash cards Data-analysis primers Glossaries

Cengage InSite for Writing and Research™—with Turnitin® Originality Checker InSite features a full suite of writing, peer review, online grading, and e-portfolio applications. It is an all-in-one tool that helps instructors manage the ﬂow of papers electronically and allows students to submit papers and peer reviews online. Also included in the suite is Turnitin, an originality checker that offers a simple solution for instructors who want a strong deterrent against plagiarism, as well as encouragement for students to employ proper research techniques. Access is available for packaging with each copy of this book. For more information, visit http://insite.cengage.com.

Acknowledgments

It would be impossible to acknowledge adequately all the people who have inﬂuenced this book. My earlier methods text, Survey Research Methods, was dedicated to Samuel Stouffer, Paul Lazarsfeld, and Charles Glock. I again acknowledge my debt to them. I also repeat my thanks to those colleagues acknowledged for their comments during the writing of the ﬁrst, second, and third editions of this book. The present book still reﬂects their contributions. Many other colleagues helped me revise the book as well—including the amazing 110 instructors who took the time to respond to our electronic survey. Their feedback was invaluable. I also particularly want to thank the instructors who reviewed the manuscript of this edition and made helpful suggestions:

Marian A. O. Cohen, Framingham State College Kimberly Dugan, Eastern Connecticut State University Craig Forsyth, University of Louisiana at Lafayette Herman Gibson, Henderson State University Ellen Goldring, Peabody College, Vanderbilt Susan Gore, University of Massachusetts at Boston Sarah Hurley, Arkansas State University Jana L. Jasinski, University of Central Florida Robert Kleidman, Cleveland State University Michael Kleiman, University of South Florida Augustine Kposowa, University of California, Riverside

Emily Barman, Boston University

Marci B. Littleﬁeld, Indiana State University

Dale Brooker, Saint Joseph’s College of Maine Dwight Haase, University of Dayton

Patrick F. McManimon, Jr., William Patterson University

Linda Lindsey, Maryville University

Jeanne Mekolichick, Radford University

Elizabeth Monk-Turner, Old Dominion University

Jared Schultz, Texas Tech University Health Sciences Center

Sunil Thankam, The University of Texas at San Antonio

Bruce H. Wade, Spelman College

Also, I appreciate the insights and assistance of those who reviewed the previous edition: Victor Agadjanian, Arizona State University Melanie Arthur, Portland State University

Thomas C. Wilson, Florida Atlantic University Gary Wyatt, Emporia State University I would also like to thank survey participants who took the time to provide valuable information on several features of the book:

Pat Christian, Canisius College

James T. Ault, III, Creighton University

William T. Clute, University of Nebraska at Omaha

Paul Calarco, SUNY at Albany xxiii

Acknowledgments Roy Childs, University of the Paciﬁc Liz Depoy, University of Maine Pat Fisher, University of Tennessee Robert Gardner, Bowdoin College Elizabeth Jones, California University of Pennsylvania Barbara Keating, Minnesota State University, Mankato J. David Martin, Midwestern State University Patrick A. Moore, University of Great Falls I also wish to thank Anne Baird, Morehouse College; Rae Banks, Syracuse University; Roland Chilton, University of Massachusetts, Amherst; M. Richard Cramer, University of North Carolina, Chapel Hill; Joseph Fletcher, University of Toronto; Shaul Gabbay, University of Illinois, Chicago; Marcia Ghidina, University of North Carolina, Asheville; Roland Hawkes, Southern Illinois University; Jeffrey Jacques, Florida A&M University; Daniel J. Klenow, North Dakota State University; Wanda Kosinski, Ramapo College, New Jersey; Manfred Kuechler, CUNY Hunter College; Cecilia Menjívar, Arizona State University; Joan Morris, University of Central Florida; Alisa Potter, Concordia College; Zhenchoa Qian, Arizona State University; Robert W. Reynolds, Weber State University; Laurie K. Scheuble, Doane College; Beth Anne Shelton, University of Texas, Arlington; Matthew Sloan, University of Wisconsin, Madison; Bernard Sorofman, University of Iowa; Ron Stewart; Randy Stoecker, University of Toledo; Theodore Wagenaar, Miami University, Ohio; Robert Wolf, Eastern Connecticut State University; and Jerome Wolfe, University of Miami. Over the years, I’ve become more and more impressed by the important role played by editors in books like this. Although an author’s name appears on the book’s spine, much of its backbone derives from the strength of its editors. Since 1973 I’ve worked with many sociology editors at Wadsworth, which has involved the kinds of adjustments you might need to make in successive marriages. The quality of a book like this depends

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particularly on the wisdom, creativity, and perspiration of the acquisitions editor and the development editor, in this case Chris Caldeira and Dan Moneypenny, respectively. I am very grateful for their efforts on this book, and you should be, too. There are also others at Wadsworth whose talents have had an impact on this book. I would like to acknowledge Meghan Pease for her inspired marketing efforts, making sure everyone on the planet is aware of the book; Lauren Keyes for her work on the website and other technology supplements; Erin Parkins for managing the development of all of the useful print supplements to round out the teaching package; and Cheri Palmer for shepherding the countless pieces and people required to turn a manuscript into a book. I also wish to thank Greg Hubit for managing all the critical production processes with great skill. Molly Roth is the standard by which copy editors should be judged, though that might set the standard too high. Molly and I have worked together on several books now, and she is simply the best. She successfully walks the thin line that separates a reluctance to say the author failed and a delight in saying it. I have never felt she let me get away with anything, nor have I felt anything but the highest support for my intention. Somehow, Molly can see what I’m trying to say and can often ﬁnd ways of saying it more clearly and more powerfully. Ted Wagenaar has contributed extensively to this book. Ted and I coauthor the accompanying student study guide, Guided Activities for Practicing Social Research, but that’s only the tip of the iceberg. Ted is a cherished colleague, welcome critic, good friend, and altogether decent human being. I have dedicated this book to my soul mate, best friend, and wife, Suzanne Babbie. The fact that she became my wife during the course of this revision makes it all the more ﬁtting. I see in Suze those things I am most proud of in myself, except I see purer versions of those qualities in her. She ennobles what is possible in a human being, and I become a better person because of her example.

The Practice of Social Research

Human Inquiry and Science

Paradigms, Theory, and Social Research

The Ethics and Politics of Social Research

cience is a familiar word; everyone uses it. Yet, images of science differ greatly. For some, science is mathematics; for others, it’s white coats and laboratories. It’s often confused with technology or equated with tough high school or college courses. Science is, of course, none of these things per se. It is difﬁcult, however, to specify exactly what science is. Scientists themselves disagree on the proper deﬁnition. For the purposes of this book, we look at science as a method of inquiry—a way of learning and knowing things about the world around us. Contrasted with other ways of learning and knowing about the world, science has some special characteristics. It is a conscious, deliberate, and rigorous undertaking. Sometimes it uses statistical analyses, but often it does not. We’ll examine these and other traits in this opening set of chapters. Dr. Benjamin Spock, the renowned author and pediatrician, began his books on child care by assuring new parents that they already know more about child care than they think they do. I want to begin this book on a

PA RT 1

An Introduction to Inquiry similar note. Before you’ve read very far, you will realize that you already know a great deal about the practice of social research. In fact, you’ve been conducting research all your life. From that perspective, the purpose of this book is to help you sharpen skills you already have and perhaps to show you some tricks that may not have occurred to you. Part 1 of this book lays the groundwork for the rest of the book by examining the fundamental characteristics and issues that make science different from other ways of knowing things. In Chapter 1, we’ll begin with a look at native human inquiry, the sort of thing you’ve been doing all your life. In the course of that examination, we’ll see some of the ways people go astray in trying to understand the world around them, and I’ll summarize the primary characteristics of scientiﬁc inquiry that guard against those errors. Chapter 2 deals with social theories and the links between theory and research. We’ll look at some of the

theoretical paradigms that shape the nature of inquiry and that largely determine what scientists look for and how they interpret what they see. Whereas most of this book deals with the scientiﬁc concerns of social research, Chapter 3 introduces two other important concerns: the ethics and politics of research. Researchers are governed by a set of ethical constraints that reﬂect ideals and values aimed at helping, not harming, people. Social research is also shaped by the fact that it operates within the political codes and systems of the societies it seeks to study and understand. These two topics appear throughout the book as critical components of social research. The overall purpose of Part 1 is to construct a backdrop against which to view the speciﬁcs of research design and execution. After completing Part 1, you’ll be ready to look at some of the more concrete aspects of social research.

CHAPTER ONE

Human Inquiry and Science

CHAPTER OVERVIEW

All of us try to understand and predict the social world. Scientiﬁc inquiries—and social research in particular—are designed to avoid the pitfalls of ordinary human inquiry. Introduction Looking for Reality Knowledge from Agreement Reality Errors in Inquiry, and Some Solutions What’s Really Real? The Foundations of Social Science Theory, Not Philosophy or Belief Social Regularities Aggregates, Not Individuals Concepts and Variables

The Purposes of Social Research The Ethics of Human Inquiry Some Dialectics of Social Research Idiographic and Nomothetic Explanation Inductive and Deductive Theory Qualitative and Quantitative Data Pure and Applied Research The Research Proposal

CengageNOW for Sociology 2

Use this online tool to help you make the grade on your next exam. After reading this chapter, go to “Online Study Resources” at the end of the chapter for instructions on how to beneﬁt from CengageNOW.

Introduction

Introduction This book is about knowing things—not so much what we know as how we know it. Let’s start by examining a few things you probably know already. You know the world is round. You probably also know it’s cold on the dark side of the moon, and you know people speak Chinese in China. You know that vitamin C can prevent colds and that unprotected sex can result in AIDS. How do you know? Unless you’ve been to the dark side of the moon lately or done experimental research on the virtues of vitamin C, you know these things because somebody told them to you, and you believed what you were told. You may have read in National Geographic that people speak Chinese languages in China, and because that made sense to you, you didn’t question it. Perhaps your physics or astronomy instructor told you it was cold on the dark side of the moon, or maybe you heard it on National Public Radio (NPR). Some of the things you know seem absolutely obvious to you. If someone asked you how you know the world is round, you’d probably say, “Everybody knows that.” There are a lot of things everybody knows. Of course, everyone used to “know” that the world was ﬂat. Most of what you and I know is a matter of agreement and belief. Little of it is based on personal experience and discovery. A big part of growing up in any society, in fact, is the process of learning to accept what everybody around us “knows” is so. If you don’t know those same things, you can’t really be a part of the group. If you were to question seriously whether the world is really round, you’d quickly ﬁnd yourself set apart from other people. You might be sent to live in a hospital with other people who question things like that. Although most of what we know is a matter of believing what we’ve been told, there is nothing wrong with us in that respect. It’s simply the way human societies are structured, and it’s a quite useful quality. The basis of knowledge is agreement. Because we can’t learn all we need to know

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by means of personal experience and discovery alone, things are set up so we can simply believe what others tell us. We know some things through tradition and some things from “experts.” I’m not saying you should never question this received knowledge; I’m just drawing your attention to the way you and society normally get along regarding what’s so. There are other ways of knowing things, however. In contrast to knowing things through agreement, we can know them through direct experience—through observation. If you dive into a glacial stream ﬂowing through the Canadian Rockies, you don’t need anyone to tell you it’s cold. The ﬁrst time you stepped on a thorn, you knew it hurt before anyone told you. When our experience conﬂicts with what everyone else knows, though, there’s a good chance we’ll surrender our experience in favor of the agreement. Let’s take an example. Imagine you’ve come to a party at my house. It’s a high-class affair, and the drinks and food are excellent. In particular, you’re taken by one of the appetizers I bring around on a tray: a breaded, deep-fried appetizer that’s especially zesty. You have a couple—they’re so delicious! You have more. Soon you’re subtly moving around the room to be wherever I am when I arrive with a tray of these nibblies. Finally, you can’t contain yourself any more. “What are they?” you ask. “How can I get the recipe?” And I let you in on the secret: “You’ve been eating breaded, deep-fried worms!” Your response is dramatic: Your stomach rebels, and you throw up all over the living-room rug. Argh! What a terrible thing to serve guests! The point of the story is that both of your feelings about the appetizer were quite real. Your initial liking for them, based on your own direct experience, was certainly real. But so was your feeling of disgust when you found out that you’d been eating worms. It should be evident, however, that this feeling of disgust was strictly a product of the agreements you have with those around you

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that worms aren’t ﬁt to eat. That’s an agreement you entered into the ﬁrst time your parents found you sitting in a pile of dirt with half of a wriggling worm dangling from your lips. When they pried your mouth open and reached down your throat in search of the other half of the worm, you learned that worms are not acceptable food in our society. Aside from these agreements, what’s wrong with worms? They are probably high in protein and low in calories. Bite-sized and easily packaged, they are a distributor’s dream. They are also a delicacy for some people who live in societies that lack our agreement that worms are disgusting. Some people might love the worms but be turned off by the deep-fried breading. Here’s another question to consider: “Are worms ‘really’ good or ‘really’ bad to eat?” And here’s a more interesting question: “How could you know which was really so?” This book is about answering the second kind of question. The rest of this chapter looks at how we know what is real. We’ll begin by examining inquiry as a natural human activity, something we all have engaged in every day of our lives. We’ll look at the source of everyday knowledge and at some kinds of errors we make in normal inquiry. We’ll then examine what makes science—in particular, social science—different. After considering some of the underlying ideas of social research, we’ll conclude with an initial consideration of issues in social research.

Looking for Reality Reality is a tricky business. You probably already suspect that some of the things you “know” may not be true, but how can you really know what’s real? People have grappled with this question for thousands of years.

epistemology The science of knowing; systems of knowledge. methodology The science of ﬁnding out; procedures for scientiﬁc investigation.

Knowledge from Agreement Reality One answer that has arisen out of that grappling is science, which offers an approach to both agreement reality and experiential reality. Scientists have certain criteria that must be met before they will accept the reality of something they have not personally experienced. In general, a scientiﬁc assertion must have both logical and empirical support: It must make sense, and it must not contradict actual observation. Why do earthbound scientists accept the assertion that the dark side of the moon is cold? First, it makes sense, because the moon’s surface heat comes from the sun’s rays, and the dark side of the moon is dark because it’s always turned away from the sun. Second, scientiﬁc measurements made on the moon’s dark side conﬁrm this logical expectation. So, scientists accept the reality of things they don’t personally experience— they accept an agreement reality—but they have special standards for doing so. More to the point of this book, however, science offers a special approach to the discovery of reality through personal experience. In other words, it offers a special approach to the business of inquiry. Epistemology is the science of knowing; methodology (a subﬁeld of epistemology) might be called the science of ﬁnding out. This book presents and examines social science methodology, or how social scientists ﬁnd out about human social life. Why do we need social science to discover the reality of social life? To ﬁnd out, let’s start by considering what happens in ordinary, nonscientiﬁc inquiry.

Ordinary Human Inquiry Practically all people, and many other animals as well, exhibit a desire to predict their future circ*mstances. Humans seem predisposed to undertake this task by using causal and probabilistic reasoning. First, we generally recognize that future circ*mstances are somehow caused or conditioned by present ones. We learn that getting an education will affect how much money we earn later in life

Looking for Reality and that swimming beyond the reef may bring an unhappy encounter with a shark. Sharks, on the other hand—whether or not they reason the matter through—may learn that hanging around the reef often brings a happy encounter with unhappy swimmers. Second, we also learn that such patterns of cause and effect are probabilistic. That is, the effects occur more often when the causes occur than when the causes are absent—but not always. Thus, students learn that studying hard produces good grades in most instances, but not every time. We recognize the danger of swimming beyond the reef, without believing that every such swim will be fatal. As we’ll see throughout the book, science makes these concepts of causality and probability more explicit and provides techniques for dealing with them more rigorously than casual human inquiry does. It sharpens the skills we already have by making us more conscious, rigorous, and explicit in our inquiries. In looking at ordinary human inquiry, we need to distinguish between prediction and understanding. Often, we can make predictions without understanding—perhaps you can predict rain when your trick knee aches. And often, even if we don’t understand why, we’re willing to act on the basis of a demonstrated predictive ability. A racetrack buff who discovers that the third-ranked horse in the third race of the day always seems to win will probably keep betting without knowing, or caring, why it works out that way. Of course, the drawback in predicting without understanding will become powerfully evident when one of the other horses wins and our buff loses a week’s pay. Whatever the primitive drives or instincts that motivate human beings and other animals, satisfying these drives depends heavily on the ability to predict future circ*mstances. For people, however, the attempt to predict is often placed in a context of knowledge and understanding. If you can understand why things are related to each other, why certain regular patterns occur, you can predict better than if you simply observe and remember those patterns. Thus, human inquiry aims at answering both “what” and “why” questions, and we pursue these goals by observing and ﬁguring out.

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As I suggested earlier in this chapter, our attempts to learn about the world are only partly linked to direct personal inquiry or experience. Another, much larger, part comes from the agreed-on knowledge that others give us, those things “everyone knows.” This agreement reality both assists and hinders our attempts to ﬁnd out for ourselves. To see how, consider two important sources of our secondhand knowledge—tradition and authority.

Tradition Each of us inherits a culture made up, in part, of ﬁrmly accepted knowledge about the workings of the world and the values that guide our participation in it. We may learn from others that planting corn in the spring will garner the greatest assistance from the gods, that eating too much candy will decay our teeth, that the circumference of a circle is approximately twenty-two sevenths of its diameter, or that masturbation will blind us. Ideas about gender, race, religion, and different nations that you learned as you were growing up would ﬁt in this category. We may test a few of these “truths” on our own, but we simply accept the great majority of them. These are the things that “everybody knows.” Tradition, in this sense of the term, offers some clear advantages to human inquiry. By accepting what everybody knows, we avoid the overwhelming task of starting from scratch in our search for regularities and understanding. Knowledge is cumulative, and an inherited body of information and understanding is the jumping-off point for the development of more knowledge. We often speak of “standing on the shoulders of giants,” that is, on those of previous generations. At the same time, tradition may hinder human inquiry. If we seek a fresh understanding of something everybody already understands and has always understood, we may be marked as fools for our efforts. More to the point, however, it rarely occurs to most of us to seek a different understanding of something we all “know” to be true.

agreement reality Those things we “know” as part of the culture we share with those around us.

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Authority Despite the power of tradition, new knowledge appears every day. Quite aside from our own personal inquiries, we beneﬁt throughout our lives from new discoveries and understandings produced by others. Often, acceptance of these new acquisitions depends on the status of the discoverer. You’re more likely to believe that the common cold can be transmitted through kissing, for example, when you hear it from an epidemiologist than when you hear it from your uncle Pete (unless, of course, he’s also an epidemiologist). Like tradition, authority can both assist and hinder human inquiry. We do well to trust the judgment of the person who has special training, expertise, and credentials in a given matter, especially in the face of controversy. At the same time, inquiry can be greatly hindered by the legitimate authorities who err within their own province. Biologists, after all, make their mistakes in the ﬁeld of biology. Moreover, biological knowledge changes over time. Inquiry is also hindered when we depend on the authority of experts speaking outside their realm of expertise. For example, consider the political or religious leader with no medical or biochemical expertise who declares that marijuana can fry your brain. The advertising industry plays heavily on this misuse of authority by, for example, having popular athletes discuss the nutritional value of breakfast cereals or having movie actors evaluate the performance of automobiles. Both tradition and authority, then, act as double-edged swords in the search for knowledge about the world. Simply put, they provide us with a starting point for our own inquiry, but they can lead us to start at the wrong point and push us off in the wrong direction.

Errors in Inquiry, and Some Solutions Besides the potential dangers of tradition and authority, other pitfalls often cause us to stumble and fall when we set out to learn for ourselves. Let’s look at some of the common errors we make in

our casual inquiries and at the ways science guards against those errors.

Inaccurate Observations Quite frequently, we make mistakes in our observations. For example, what was your methodology instructor wearing on the ﬁrst day of class? If you have to guess, it’s because most of our daily observations are casual and semiconscious. That’s why we often disagree about what really happened. In contrast to casual human inquiry, scientiﬁc observation is a conscious activity. Just making observation more deliberate helps reduce error. If you had to guess what your instructor was wearing on the ﬁrst day of class, you’d probably make a mistake. If you’d gone to the ﬁrst class with a conscious plan to observe and record what your instructor was wearing, however, you’d be far more likely to be accurate. (You might also need a hobby.) In many cases, both simple and complex measurement devices help guard against inaccurate observations. Moreover, they add a degree of precision well beyond the capacity of the unassisted human senses. Suppose, for example, that you’d taken color photographs of your instructor that day. (See earlier comment about needing a hobby.)

Overgeneralization When we look for patterns among the speciﬁc things we observe around us, we often assume that a few similar events provide evidence of a general pattern. That is, we overgeneralize on the basis of limited observations. (Think back to our now-broke racetrack buff.) Probably the tendency to overgeneralize peaks when the pressure to arrive at a general understanding is high. Yet it also occurs without such pressure. Whenever overgeneralization does occur, it can misdirect or impede inquiry. Imagine you are a reporter covering an animalrights demonstration. You have orders to turn in your story in just two hours, and you need to know why people are demonstrating. Rushing to the scene, you start interviewing them, asking for their reasons. The ﬁrst three demonstrators you

Looking for Reality interview give you essentially the same reason, so you simply assume that the other 3,000 are also there for that reason. Unfortunately, when your story appears, your editor gets scores of letters from protesters who were there for an entirely different reason. Scientists often guard against overgeneralization by committing themselves in advance to a sufﬁciently large and representative sample of observations. Another safeguard is provided by the replication of inquiry. Basically, replication means repeating a study and checking to see whether the same results are produced each time. Then, as a further test, the study may be repeated again under slightly varied conditions.

Selective Observation One danger of overgeneralization is that it can lead to selective observation. Once we have concluded that a particular pattern exists and have developed a general understanding of why it exists, we tend to focus on future events and situations that ﬁt the pattern, and we tend to ignore those that do not. Racial and ethnic prejudices depend heavily on selective observation for their persistence. Sometimes a research design will specify in advance the number and kind of observations to be made as a basis for reaching a conclusion. If we wanted to learn whether women were more likely than men to support freedom to choose an abortion, we would commit ourselves to making a speciﬁed number of observations on that question in a research project. We might select a thousand carefully chosen people to be interviewed on the issue. Alternately, when making direct observations of an event, such as attending the animal-rights demonstration, we might make a special effort to ﬁnd “deviant cases”—precisely those who do not ﬁt into the general pattern. Concluding that one youth became delinquent largely because of a lack of positive adult role models draws attention to the part that role models play in keeping most youths on the straight and narrow. In this recollection of growing up in rural Vermont, Lewis Hill (2000: 35) presents another example of selective observation:

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Haying began right after the Fourth of July. The farmers in our neighborhood believed that anyone who started earlier was sure to suffer all the storms of late June in addition to those following the holiday which the old-timers said were caused by all the noise and smoke of gunpowder burning. My mother told me that my grandfather and other Civil War veterans claimed it always rained hard after a big battle. Things didn’t always work out the way the older residents promised, of course, but everyone remembered only the times they did.

Illogical Reasoning There are other ways in which we often deal with observations that contradict our understanding of the way things are in daily life. Surely one of the most remarkable creations of the human mind is “the exception that proves the rule.” That idea doesn’t make any sense at all. An exception can draw attention to a rule or to a supposed rule (in its original meaning, “prove” meant “test”), but in no system of logic can it validate the rule it contradicts. Even so, we often use this pithy saying to brush away contradictions with a simple stroke of illogic. What statisticians have called the gambler’s fallacy is another illustration of illogic in day-to-day reasoning. Often we assume that a consistent run of either good or bad luck foreshadows its opposite. An evening of bad luck at poker may kindle the belief that a winning hand is just around the corner. Many a poker player has stayed in a game much too long because of that mistaken belief. Conversely, an extended period of good weather may lead you to worry that rain will certainly ruin the weekend picnic. Although all of us sometimes fall into embarrassingly illogical reasoning, scientists try to avoid this pitfall by using systems of logic consciously and explicitly. We’ll examine the logic of science more deeply in Chapter 2. For now, simply note that

replication Repeating a research study to test and either conﬁrm or question the ﬁndings of an earlier study.

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logical reasoning is a conscious activity for scientists and that other scientists are always around to keep them honest. Science, then, attempts to protect its inquiries from the common pitfalls of ordinary inquiry. Accurately observing and understanding reality is not an obvious or trivial matter. Indeed, it’s more complicated than I’ve suggested.

What’s Really Real?

the wicked tree thing; in fact, the second tribe felt that the spirits in the tree were holy and beneﬁcial. The discovery of this diversity led members of the ﬁrst tribe to conclude that “some tribes I could name are pretty stupid.” For them, the tree was still wicked, and they expected that some misguided people would soon be moving to Toad City.

The Modern View

Philosophers sometimes use the phrase naive realism to describe the way most of us operate in our daily lives. When you sit at a table to write, you probably don’t spend a lot of time thinking about whether the table is made up of atoms, which in turn are mostly empty space. When you step into the street and see a city bus hurtling down on you, it’s not the best time to reﬂect on methods for testing whether the bus really exists. We all live with a view that what’s real is pretty obvious—and that view usually gets us through the day. I don’t want this book to interfere with your ability to deal with everyday life. I hope, however, that the preceding discussions have demonstrated that the nature of “reality” is perhaps more complex than we tend to assume in our everyday functioning. Here are three views on reality that will provide a philosophical backdrop for the discussions of science to follow. They are sometimes called premodern, modern, and postmodern views of reality (W. Anderson 1990).

What philosophers call the modern view accepts such diversity as legitimate, a philosophical “different strokes for different folks.” As a modern thinker, you would say, “I regard the spirits in the tree as evil, but I know that others regard them as good. Neither of us is right or wrong. There are simply spirits in the tree. They are neither good nor evil, but different people have different ideas about them.” Adopting the modern view is easy for most of us. Some might regard a dandelion as a beautiful ﬂower, whereas others see only an annoying weed. In the premodern view, a dandelion has to be either one or the other. If you think it is a weed, it is really a weed, though you may admit that some people have a warped sense of beauty. In the modern view, a dandelion is simply a dandelion. It is a plant with yellow petals and green leaves. The concepts “beautiful ﬂower” and “annoying weed” are subjective points of view imposed on the plant by different people. Neither is a quality of the plant itself, just as “good” and “evil” were concepts imposed on the spirits in the tree in our example.

The Premodern View

The Postmodern View

This view of reality has guided most of human history. Our early ancestors all assumed that they saw things as they really were. In fact, this assumption was so fundamental that they didn’t even see it as an assumption. No cavemom said to her cavekid, “Our tribe makes an assumption that evil spirits reside in the Old Twisted Tree.” No, she said, “STAY OUT OF THAT TREE OR YOU’LL TURN INTO A TOAD!” As humans evolved and became aware of their diversity, they came to recognize that others did not always share their views of things. Thus, they may have discovered that another tribe didn’t buy

Increasingly, philosophers speak of a postmodern view of reality. In this view, the spirits don’t exist. Neither does the dandelion. All that’s “real” are the images we get through our points of view. Put differently, there’s nothing “out there”; it’s all “in here.” As Gertrude Stein said of the city of Oakland, “There’s no there, there.” No matter how bizarre the postmodern view may seem to you on ﬁrst reﬂection, it has a certain ironic inevitability. Take a moment to notice the book you are reading; notice speciﬁcally what it looks like. Because you are reading these words, it probably looks something like Figure 1-1a.

Looking for Reality

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FIGURE 1-1 A book. All of these are the same book, but it looks different when viewed from different locations, perspectives, or “points of view.”

Does Figure 1-1a represent the way your book “really” looks? Or does it merely represent what the book looks like from your current point of view? Surely, Figures 1-1b, c, and d are equally valid representations. But these views of the book differ greatly from each other. Which is the “reality”? As this example illustrates, there is no answer to the question “What does the book really look like?” All we can offer is the different ways it looks from different points of view. Thus, according to the postmodern view, there is no “book,” only various images of it from different points of view. And all the different images are equally “true.” Now let’s apply this logic to a social situation. Imagine a husband and wife arguing. When she looks over at her quarreling husband, Figure 1-2 is what the wife sees. Take a minute to imagine what you would feel and think if you were the woman in this drawing. How would you explain later to your best friend what had happened? What solutions to the conﬂict would seem appropriate if you were this woman? Of course, what the woman’s husband sees is another matter altogether, as shown in Figure 1-3. Take a minute to imagine experiencing the situation from his point of view. What thoughts and feelings would you have? How would you tell your

FIGURE 1-2 Wife’s Point of View. There is no question in the wife’s mind as to who is right and rational and who is out of control.

FIGURE 1-3 Husband’s Point of View. The husband has a very different perception of the same set of events, of course. best friend what had happened? What solutions would seem appropriate for resolving the conﬂict? Now consider a third point of view. Suppose you were an outside observer, watching this interaction between a wife and husband. What would it look like to you now? Unfortunately,

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we can’t easily portray the third point of view without knowing something about the personal feelings, beliefs, past experiences, and so forth that you would bring to your task as outside observer. (Though I call you an “outside” observer, you would be, of course, observing from inside your own mental system.) To take an extreme example, if you were a conﬁrmed male chauvinist, you’d probably see the ﬁght pretty much the same way that the husband saw it. On the other hand, if you were committed to the view that men are generally unreasonable bums, you’d see things the way the wife saw them in the earlier picture. Imagine that instead you see two unreasonable people quarreling irrationally with each other. Would you see them both as irresponsible jerks, equally responsible for the conﬂict? Or would you see them as two people facing a difﬁcult human situation, each doing the best he or she can to resolve it? Imagine feeling compassion for them and noticing how each of them attempts to end the hostility, even though the gravity of the problem keeps them ﬁghting. Notice how different these several views are. Which is a “true” picture of what is happening between the wife and the husband? You win the prize if you notice that the personal viewpoint you bring to the observational task will again color your perception of what is happening. The postmodern view represents a critical dilemma for scientists. Although their task is to observe and understand what is “really” happening, they are all human and, as such, bring along personal orientations that will color what they observe and how they explain it. There is ultimately no way people can totally step outside their humanness to see and understand the world as it “really” is—that is, independently of all human viewpoints. Whereas the modern view acknowledges the inevitability of human subjectivity, the postmodern

theory A systematic explanation for the observations that relate to a particular aspect of life: juvenile delinquency, for example, or perhaps social stratiﬁcation or political revolution.

view suggests there is actually no “objective” reality to be observed in the ﬁrst place. There are only our several subjective views. You may want to ponder these three views of reality on your own for awhile. We’ll return to them in Chapter 2 when we focus on speciﬁc scientiﬁc paradigms. Ultimately, two points will emerge. First, established scientiﬁc procedures sometimes allow us to deal effectively with this dilemma—that is, we can study people and help them through their difﬁculties without being able to view “reality” directly. Second, different philosophical stances suggest a powerful range of possibilities for structuring our research. Let’s turn now from general philosophical ideas to the foundations of social science approaches to understanding. A consideration of these underpinnings of social research will prepare the way for our exploration of speciﬁc research techniques.

The Foundations of Social Science Science is sometimes characterized as logicoempirical. This ungainly term carries an important message: As we noted earlier, the two pillars of science are logic and observation. That is, a scientiﬁc understanding of the world must both make sense and correspond to what we observe. Both elements are essential to science and relate to the three major aspects of the enterprise of social science: theory, data collection, and data analysis. To oversimplify just a bit, scientiﬁc theory deals with the logical aspect of science—providing systematic explanations—whereas data collection deals with the observational aspect. Data analysis looks for patterns in observations and, where appropriate, compares what is logically expected with what is actually observed. Although this book is primarily about data collection and data analysis—that is, how to conduct social research—the rest of Part 1 is devoted to the theoretical context of research. Parts 2 and 3 then focus on data collection, and Part 4 offers an introduction to the analysis of data. Underlying the concepts presented in the rest of the book are some fundamental ideas that

The Foundations of Social Science distinguish social science—theory, data collection, and analysis—from other ways of looking at social phenomena. Let’s consider these ideas.

Theory, Not Philosophy or Belief Today, social theory has to do with what is, not with what should be. For many centuries, however, social theory did not distinguish between these two orientations. Social philosophers liberally mixed their observations of what happened around them, their speculations about why, and their ideas about how things ought to be. Although modern social researchers may do the same from time to time, as scientists they focus on how things actually are and why. This means that scientiﬁc theory—and, more broadly, science itself—cannot settle debates about values. Science cannot determine whether capitalism is better or worse than socialism. What it can do is determine how these systems perform, but only in terms of some set of agreed-on criteria. For example, we could determine scientiﬁcally whether capitalism or socialism most supports human dignity and freedom only if we ﬁrst agreed on some measurable deﬁnitions of dignity and freedom. Our conclusions would then be limited to the meanings speciﬁed in our deﬁnitions. They would have no general meaning beyond that. By the same token, if we could agree that suicide rates, say, or giving to charity were good measures of the quality of a religion, then we could determine scientiﬁcally whether Buddhism or Christianity is the better religion. Again, our conclusion would be inextricably tied to our chosen criteria. As a practical matter, people seldom agree on precise criteria for determining issues of value, so science is seldom useful in settling such debates. In fact, questions like these are so much a matter of opinion and belief that scientiﬁc inquiry is often viewed as a threat to what is “already known.” We’ll consider this issue in more detail in Chapter 12, when we look at evaluation research. As you’ll see, researchers have become increasingly involved in studying social programs that reﬂect ideological points of view, such as afﬁrmative action or welfare reform. One of the biggest problems

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they face is getting people to agree on criteria of success and failure. Yet such criteria are essential if social research is to tell us anything useful about matters of value. By analogy, a stopwatch cannot tell us if one sprinter is better than another unless we ﬁrst agree that speed is the critical criterion. Social science, then, can help us know only what is and why. We can use it to determine what ought to be, but only when people agree on the criteria for deciding what outcomes are better than others—an agreement that seldom occurs. As I indicated earlier, even knowing “what is and why” is no simple task. Let’s turn now to some of the fundamental ideas that underlie social science’s efforts to describe and understand social reality.

Social Regularities In large part, social research aims to ﬁnd patterns of regularity in social life. Although all the sciences share that aim, it sometimes imposes a barrier for people when they ﬁrst approach social science. Certainly at ﬁrst glance the subject matter of the physical sciences seems to be more governed by regularities than does that of the social sciences. A heavy object falls to earth every time we drop it, but a person may vote for a particular candidate in one election and against that same candidate in the next. Similarly, ice always melts when heated enough, but habitually honest people sometimes steal. Despite such examples, however, social affairs do exhibit a high degree of regularity that research can reveal and theory can explain. To begin with, the tremendous number of formal norms in society create a considerable degree of regularity. For example, trafﬁc laws in the United States induce the vast majority of people to drive on the right side of the street rather than the left. Registration requirements for voters lead to some predictable patterns in which classes of people vote in national elections. Labor laws create a high degree of uniformity in the minimum age of paid workers as well as the minimum amount they are paid. Such formal prescriptions regulate, or regularize, social behavior.

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Aside from formal prescriptions, we can observe other social norms that create more regularities. Among registered voters, Republicans are more likely than Democrats to vote for Republican candidates. University professors tend to earn more money than unskilled laborers do. Men tend to earn more than women. And so on. Three objections are sometimes raised in regard to such social regularities. First, some of the regularities may seem trivial. For example, Republicans vote for Republicans; everyone knows that. Second, contradictory cases may be cited, indicating that the “regularity” isn’t totally regular. Some laborers make more money than some professors do. Third, it may be argued that, unlike the heavy objects that cannot decide not to fall when dropped, the people involved in the regularity could upset the whole thing if they wanted to. Let’s deal with each of these objections in turn.

The Charge of Triviality During World War II, Samuel Stouffer, one of the greatest social science researchers, organized a research branch in the U.S. Army to conduct studies in support of the war effort (Stouffer et al. 1949–1950). Many of the studies focused on the morale among soldiers. Stouffer and his colleagues found there was a great deal of “common wisdom” regarding the bases of military morale. Much of their research was devoted to testing these “obvious” truths. For example, people had long recognized that promotions affect morale in the military. When military personnel get promotions and the promotion system seems fair, morale rises. Moreover, it makes sense that people who are getting promoted will tend to think the system is fair, whereas those passed over will likely think the system is unfair. By extension, it seems sensible that soldiers in units with slow promotion rates will tend to think the system is unfair, and those in units with rapid promotions will think the system is fair. But was this the way they really felt? Stouffer and his colleagues focused their studies on two units: the Military Police (MPs), which had the slowest promotions in the Army, and the Army Air Corps (forerunner of the U.S. Air Force), which

had the fastest promotions. It stood to reason that MPs would say the promotion system was unfair, and the air corpsmen would say it was fair. The studies, however, showed just the opposite. Notice the dilemma faced by a researcher in a situation such as this. On the one hand, the observations don’t seem to make sense. On the other hand, an explanation that makes obvious good sense isn’t supported by the facts. A lesser person would have set the problem aside “for further study.” Stouffer, however, looked for an explanation for his observations, and eventually he found it. Robert Merton and other sociologists at Columbia University had begun thinking and writing about something they called reference group theory. This theory says that people judge their lot in life less by objective conditions than by comparing themselves with others around them—their reference group. For example, if you lived among poor people, a salary of $50,000 a year would make you feel like a millionaire. But if you lived among people who earned $500,000 a year, that same $50,000 salary would make you feel impoverished. Stouffer applied this line of reasoning to the soldiers he had studied. Even if a particular MP had not been promoted for a long time, it was unlikely that he knew some less-deserving person who had gotten promoted more quickly. Nobody got promoted in the MPs. Had he been in the Air Corps— even if he had gotten several promotions in rapid succession—he would probably have been able to point to someone less deserving who had gotten even faster promotions. An MP’s reference group, then, was his fellow MPs, and the air corpsman compared himself with fellow corpsmen. Ultimately, then, Stouffer reached an understanding of soldiers’ attitudes toward the promotion system that (1) made sense and (2) corresponded to the facts. This story shows that documenting the obvious is a valuable function of any science, physical or social. Charles Darwin coined the phrase fool’s experiment to describe much of his own research— research in which he tested things that everyone else “already knew.” As Darwin understood, the obvious all too often turns out to be wrong; thus, apparent triviality is not a legitimate objection to any scientiﬁc endeavor.

The Foundations of Social Science

What about Exceptions? The objection that there are always exceptions to any social regularity does not mean that the regularity itself is unreal or unimportant. A particular woman may well earn more money than most men, but that provides small consolation to the majority of women, who earn less. The pattern still exists. Social regularities, in other words, are probabilistic patterns, and they are no less real simply because some cases don’t ﬁt the general pattern. This point applies in physical science as well as social science. Subatomic physics, for example, is a science of probabilities. In genetics, the mating of a blue-eyed person with a brown-eyed person will probably result in a brown-eyed offspring. The birth of a blue-eyed child does not destroy the observed regularity, because the geneticist states only that the brown-eyed offspring is more likely and, further, that brown-eyed offspring will be born in a certain percentage of the cases. The social scientist makes a similar, probabilistic prediction— that women overall are likely to earn less than men. Once a pattern like this is observed, the social scientist has grounds for asking why it exists.

People Could Interfere Finally, the objection that the conscious will of the actors could upset observed social regularities does not pose a serious challenge to social science. This is true even though a parallel situation does not appear to exist in the physical sciences. (Presumably, physical objects cannot violate the laws of physics, although the probabilistic nature of subatomic physics once led some observers to postulate that electrons had free will.) There is no denying that a religious, right-wing bigot could go to the polls and vote for an agnostic, left-wing African American if he wanted to upset political scientists studying the election. All voters in an election could suddenly switch to the underdog just to frustrate the pollsters. Similarly, workers could go to work early or stay home from work and thereby prevent the expected rush-hour trafﬁc. But these things do not happen often enough to seriously threaten the observation of social regularities. Social regularities, then, do exist, and social scientists can detect them and observe their effects.

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When these regularities change over time, social scientists can observe and explain those changes.

Aggregates, Not Individuals The regularities of social life that social scientists study generally reﬂect the collective behavior of many individuals. Although social scientists often study motivations that affect individuals, the individual as such is seldom the subject of social science. Instead, social scientists create theories about the nature of group, rather than individual, life. Similarly, the objects of their research are typically aggregates, or collections, rather than individuals. Sometimes the collective regularities are amazing. Consider the birthrate, for example. People have babies for a wide variety of personal reasons. Some do it because their own parents want grandchildren. Some feel it’s a way of completing their womanhood or manhood. Others want to hold their marriages together, enjoy the experience of raising children, perpetuate the family name, or achieve a kind of immortality. Still others have babies by accident. If you have fathered or given birth to a baby, you could probably tell a much more detailed, idiosyncratic story. Why did you have the baby when you did, rather than a year earlier or later? Maybe you lost your job and had to delay a year before you could afford to have the baby. Maybe you only felt the urge to become a parent after someone close to you had a baby. Everyone who had a baby last year had his or her own reasons for doing so. Yet, despite this vast diversity, and despite the idiosyncrasy of each individual’s reasons, the overall birthrate in a society—the number of live births per 1,000 population—is remarkably consistent from year to year. See Table 1-1 for recent birthrates for the United States. If the U.S. birthrate were 15.9, 35.6, 7.8, 28.9, and 16.2 in ﬁve successive years, demographers would begin dropping like ﬂies. As you can see, however, social life is far more orderly than that. Moreover, this regularity occurs without societywide regulation. No one plans how many babies will be born or determines who will have them. You do not need a permit to have a baby; in fact,

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TABLE 1-1

Birthrates, United States: 1980–2006* 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993

15.9 15.8 15.9 15.6 15.6 15.8 15.6 15.7 16.0 16.4 16.7 16.2 15.8 15.4

1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

15.0 14.6 14.4 14.2 14.3 14.2 14.4 14.1 13.9 14.1 14.0 14.0 14.3

*Live births per 1,000 population Source: U.S. Bureau of the Census, Statistical Abstract of the United States (Washington, DC: U.S. Government Printing Ofﬁce, 2008), Table 77, p. 63.

many babies are conceived unexpectedly, and some are borne unwillingly. Social science theories, then, typically deal with aggregated, not individual, behavior. Their purpose is to explain why aggregate patterns of behavior are so regular even when the individuals participating in them may change over time. We could even say that social scientists don’t seek to explain people at all. They try to understand the systems in which people operate, the systems that explain why people do what they do. The elements in such a system are not people but variables.

Concepts and Variables Our most natural attempts at understanding usually take place at the level of the concrete and idiosyncratic. That’s just the way we think.

variables Logical sets of attributes. The variable gender is made of up of the attributes male and female.

Imagine that someone says to you, “Women ought to get back into the kitchen where they belong.” You’re likely to hear that comment in terms of what you know about the speaker. If it’s your old uncle Harry who is also strongly opposed to daylight saving time, zip codes, and personal computers, you’re likely to think his latest pronouncement simply ﬁts into his rather dated point of view about things in general. If, on the other hand, the statement is muttered by an incumbent politician trailing a female challenger in an electoral race, you’ll probably explain his comment in a completely different way. In both examples, you’re trying to understand the behavior of a particular individual. Social research seeks insights into classes or types of individuals. Social researchers would want to ﬁnd out about the kind of people who share that view of women’s “proper” role. Do those people have other characteristics in common that may help explain their views? Even when researchers focus their attention on a single case study—such as a community or a juvenile gang—their aim is to gain insights that would help people understand other communities and other juvenile gangs. Similarly, the attempt to fully understand one individual carries the broader purpose of understanding people or types of people in general. When this venture into understanding and explanation ends, social researchers will be able to make sense out of more than one person. In understanding what makes a group of people hostile to women who are active outside the home, they gain insight into all the individuals who share that characteristic. This is possible because, in an important sense, they have not been studying antifeminists as much as they have been studying antifeminism. It might then turn out that Uncle Harry and the politician have more in common than ﬁrst appeared. Antifeminism is spoken of as a variable because it varies. Some people display the attitude more than others do. Social researchers are interested in understanding the system of variables that causes a particular attitude to be strong in one instance and weak in another.

The Foundations of Social Science The idea of a system composed of variables may seem rather strange, so let’s look at an analogy. The subject of a physician’s attention is the patient. If the patient is ill, the physician’s purpose is to help the patient get well. By contrast, a medical researcher’s subject matter is different—the variables that cause a disease, for example. The medical researcher may study the physician’s patient, but for the researcher, that patient is relevant only as a carrier of the disease. That is not to say that medical researchers don’t care about real people. They certainly do. Their ultimate purpose in studying diseases is to protect people from them. But in their research, they are less interested in individual patients than they are in the patterns governing the appearance of the disease. In fact, when they can study a disease meaningfully without involving actual patients, they do so. Social research, then, involves the study of variables and their relationships. Social theories are written in a language of variables, and people get involved only as the “carriers” of those variables. Variables, in turn, have what social researchers call attributes (or categories or values). Attributes are characteristics or qualities that describe an object—in this case, a person. Examples include female, Asian, alienated, conservative, dishonest, intelligent, and farmer. Anything you might say to describe yourself or someone else involves an attribute. Variables, on the other hand, are logical sets of attributes. Thus, for example, male and female are attributes, and sex or gender is the variable composed of those two attributes. The variable occupation is composed of attributes such as farmer, professor, and truck driver. Social class is a variable composed of a set of attributes such as upper class, middle class, and lower class. Sometimes it helps to think of attributes as the categories that make up a variable. (See Figure 1-4 for a schematic review of what social scientists mean by variables and attributes.) The relationship between attributes and variables forms the heart of both description and explanation in science. For example, we might describe a college class in terms of the variable gender by reporting the observed frequencies of the attributes

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Some Common Social Concepts g Youn Occu

Social

patio

rc ppe

fric

Liberal

Variable

e/et

hnic

lass

n ica

A an

Rac

class

Political

views

Plumber

ity

ale

Fem

Attributes

Age

Young, middle-aged, old

Gender

Female, male

Occupation

Plumber, lawyer, data-entry clerk . . .

Race/ethnicity

African American, Asian, Caucasian, Latino . . .

Social class

Upper, middle, lower . . .

Political views

Liberal, conservative

FIGURE 1-4 Variables and Attributes. In social research and theory, both variables and attributes represent social concepts. Variables are sets of related attributes (categories, values). male and female: “The class is 60 percent men and 40 percent women.” An unemployment rate can be thought of as a description of the variable employment status of a labor force in terms of the attributes employed and unemployed. Even the report of family income for a city is a summary of attributes composing that variable: $3,124; $10,980; $35,000; and so forth. Sometimes the meanings of the concepts that lie behind social science concepts are immediately clear. Other times they aren’t. This point is discussed in “The Hardest Hit Was . . .” The relationship between attributes and variables is more complicated in the case of explanation and gets to the heart of the variable language of scientiﬁc theory. Here’s a simple example, involving two variables, education and prejudice. For the sake of simplicity, let’s assume that the variable education has only two attributes: educated and uneducated. attributes Characteristics of people or things.

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Chapter 1: Human Inquiry and Science

The Hardest Hit Was . . .

n early 1982, a deadly storm ravaged the San Francisco Bay Area, leaving an aftermath of death, injury, and property damage. As the mass media sought to highlight the most tragic results of the storm, they sometimes focused on several people who were buried alive in a mud slide in Santa Cruz. Other times, they covered the plight of the 2,900 made homeless in Marin County. Implicitly, everyone wanted to know where the worst damage was done, but the answer was not clear. Here are some data describing the results of the storm in two counties: Marin and Santa Cruz. Look over the comparisons and see if you can determine which county was “hardest hit.” Certainly, in terms of the loss of life, Santa Cruz was the “hardest hit” of the two counties. Yet more than seven times as many people were injured in Marin as in Santa Cruz; certainly, Marin County was “hardest hit” in that regard. Or consider the number of homes destroyed (worse in Santa Cruz) or damaged (worse in Marin): It matters which you focus on. The same dilemma holds true for the value of the damage done: Should we pay more attention to private damage or public damage? So which county was “hardest hit”? Ultimately, the question as posed has no answer. Although you and I both have images in our minds about communities that are “devastated” or communities that are only “lightly touched,” these images are not precise enough to permit rigorous measurements.

Similarly, let’s give the variable prejudice two attributes: prejudiced and unprejudiced. Now let’s suppose that 90 percent of the uneducated are prejudiced, and the other 10 percent are unprejudiced. And let’s suppose that 30 percent of the educated people are prejudiced, and the other 70 percent are unprejudiced. This is illustrated in Figure 1-5a. Figure 1-5a illustrates a relationship or association between the variables education and prejudice. This relationship can be seen in terms of the pairings of attributes on the two variables. There are two predominant pairings: (1) those who are educated and unprejudiced and (2) those who are uneducated and prejudiced. Here are two other useful ways of viewing that relationship. First, let’s suppose that we play a game in which we bet on your ability to guess whether a

Business destroyed People killed People injured People displaced Homes destroyed Homes damaged Businesses destroyed Businesses damaged Private damages Public damages

Marin

Santa Cruz

$1.50 million 5 379 370 28 2,900 25 800 $65.1 million $15.0 million

$56.5 million 22 50 400 135 300 10 35 $50.0 million $56.5 million

The question can be answered only if we can specify what we mean by “hardest hit.” If we measure it by death toll, then Santa Cruz was the hardest hit. If we choose to deﬁne the variable in terms of people injured and or displaced, then Marin suffered the bigger disaster. The simple fact is that we cannot answer the question without specifying exactly what we mean by the term hardest hit. This is a fundamental requirement that will arise again and again as we attempt to measure social science variables. Data source: San Francisco Chronicle, January 13, 1982, p. 16.

person is prejudiced or unprejudiced. I’ll pick the people one at a time (not telling you which ones I’ve picked), and you have to guess whether each person is prejudiced. We’ll do it for all 20 people in Figure 1-5a. Your best strategy in this case would be to guess prejudiced each time, because 12 out of the 20 are categorized that way. Thus, you’ll get 12 right and 8 wrong, for a net success of 4. Now let’s suppose that when I pick a person from the ﬁgure, I tell you whether the person is educated or uneducated. Your best strategy now would be to guess prejudiced for each uneducated person and unprejudiced for each educated person. If you followed that strategy, you’d get 16 right and 4 wrong. Your improvement in guessing prejudice by knowing education is an illustration of what it means to say that the variables are related.

The Foundations of Social Science

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FIGURE 1-5 Relationship between Two Variables (Two Possibilities). Variables such as education and prejudice and their attributes (educated/uneducated, prejudiced/unprejudiced) are the foundation for the examination of causal relationships in social research.

Second, by contrast, let’s consider how the 20 people would be distributed if education and prejudice were unrelated to each other (Figure 1-5b). Notice that half the people are educated, and half are uneducated. Also notice that 12 of the 20 (60 percent) are prejudiced. If 6 of the 10 people in each group were prejudiced, we would conclude that the two variables were unrelated to each other. Knowing a person’s education would not be of any value to you in guessing whether that person was prejudiced.

We’ll be looking at the nature of relationships between variables in some depth in Part 4. In particular, we’ll explore some of the ways relationships can be discovered and interpreted in research analysis. For now, you need a general understanding of relationships in order to appreciate the logic of social science theories. Theories describe the relationships we might logically expect between variables. Often, the expectation involves the idea of causation. That is, a person’s attributes on one variable are expected

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Chapter 1: Human Inquiry and Science

to cause, predispose, or encourage a particular attribute on another variable. In the example just illustrated, we might theorize that a person’s being educated or uneducated causes a lesser or greater likelihood of that person seeming prejudiced. As I’ll discuss in more detail later in the book, education and prejudice in this example would be regarded as an independent variable and a dependent variable, respectively. These two concepts are implicit in causal, or deterministic, models. In this example, we assume that the likelihood of being prejudiced is determined or caused by something. In other words, prejudice depends on something else, and so it is called the “dependent” variable. What the dependent variable depends on is an independent variable, in this case, education. For the purposes of this study, education is an “independent” variable because it is independent of prejudice (that is, people’s level of education is not caused by whether or not they are prejudiced). Of course, variations in levels of education can, in turn, be found to depend on something else. People whose parents have a lot of education, for example, are more likely to get a lot of education than are people whose parents have little education. In this relationship, the subject’s education is the dependent variable, and the parents’ education is the independent variable. We can say the independent variable is the cause, the dependent variable the effect. In our discussion of Figure 1-5, we looked at the distribution of the 20 people in terms of the two variables. In constructing a social science theory, we would derive an expectation regarding the relationship between the two variables based on what we know about each. We know, for example,

that education exposes people to a wide range of cultural variation and to diverse points of view—in short, it broadens their perspectives. Prejudice, on the other hand, represents a narrower perspective. Logically, then, we might expect education and prejudice to be somewhat incompatible. We might therefore arrive at an expectation that increasing education would reduce the occurrence of prejudice, an expectation that our observations would support. Because Figure 1-5 has illustrated two possibilities—that education reduces the likelihood of prejudice or that it has no effect—you might be interested in knowing what is actually the case. There are, of course, many types of prejudice. For purposes of this illustration, let’s consider prejudice against gays and lesbians. Over the years, the General Social Survey (GSS) has asked respondents whether hom*osexual relations between two adults is “always wrong, almost always wrong, sometimes wrong, or not wrong at all.” In 2004, 56 percent of those interviewed said that hom*osexuality was always wrong. However, this response is strongly conditioned by respondents’ education, as Table 1-2 indicates. (See the box for more about the GSS.) Notice that the theory has to do with the two variables education and prejudice, not with people as such. People are the carriers of those two variables, so the relationship between the variables can only be seen when we observe people. Ultimately, however, the theory uses a language of variables. It describes the associations that we might logically expect to exist between particular attributes of different variables.

TABLE 1-2

Education and Anti-Gay Prejudice independent variable A variable with values that are not problematic in an analysis but are taken as simply given. An independent variable is presumed to cause or determine a dependent variable. dependent variable A variable assumed to depend on or be caused by another (called the independent variable). If you ﬁnd that income is partly a function of amount of formal education, income is being treated as a dependent variable.

Level of Education

Less than high school graduate High school graduate Junior college Bachelor’s degree Graduate degree

Percent saying hom*osexuality is Always Wrong

72% 62% 56% 44% 30%

Some Dialectics of Social Research

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General Social Survey (GSS)

he National Opinion Research Center (NORC) at the University of Chicago conducts a periodic national survey of American public opinion for the purpose of making such data available for analysis by the social research community. Many data examples in this book come from

The Purposes of Social Research Chapter 4 will examine the various purposes of social research in some detail, but a brief preview here will be useful. To begin, sometimes social research is a vehicle for mapping out a topic that may warrant further study later: looking into a new political or religious group, learning something about use of a new street drug, and so forth. The methods vary greatly and the conclusions are usually suggestive rather than deﬁnitive. Even so, such exploratory social research, if carefully done, can dispel some misconceptions and help focus future research. Some social research is done for the purpose of describing the state of social affairs: What is the unemployment rate? What is the racial composition of a particular city? What percentage of the population plans to vote for a particular political candidate? Careful empirical description takes the place of speculation and impressions. Often, social research has an explanatory purpose—providing reasons for phenomena in the form of causal relationships. Why do some cities have higher unemployment rates than others? Why are some people more prejudiced than others? Why are women likely to earn less than men for doing the same job? Although answers to such questions abound in ordinary, everyday discourse, some of those answers are simply wrong. Explanatory social research provides more trustworthy explanations. Later in this chapter, we’ll compare pure and applied research, but it’s worth noting here that the purpose of some research is pretty much limited to understanding, while other research efforts are

that source. You can learn more about the GSS at the ofﬁcial website maintained by the University of Michigan; go to the link at http:// www.norc.org/GSS+Website/

deliberately intended to bring about social change, creating a more workable and/or just society. Any kind of social science study, however, can change our view of society, in some cases challenging commonly accepted “truths” about certain groups of people (see “Keeping Humanity in Focus”).

The Ethics of Human Inquiry While most of this book is devoted to the logic and techniques of doing social research, you will soon discover another theme running throughout the discussion: the ethical dimension. You will learn that medical, social, and other studies of human beings have often used methods later condemned as unethical. In Chapter 3 and throughout the book, we are going to examine the various concerns that distinguish ethical from unethical research. I suspect that such ethical concerns will make more sense to you as you learn more about the actual techniques of doing research, but I want to alert you to this important issue at the outset of our journey.

Some Dialectics of Social Research There is no one way to do social research. (If there were, this would be a much shorter book.) In fact, much of the power and potential of social research lies in the many valid approaches it comprises. Four broad and interrelated distinctions, however, underlie the variety of research approaches. Although one can see these distinctions

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Keeping Humanity in Focus s we have seen, a wide variety of research approaches can enhance our grasp of social dynamics. Much social research involves the analysis of masses of statistical data. As valuable as the examination of overall patterns can be, it can come at the risk of losing sight of the individual men and women those data represent. As such, some social research focuses speciﬁcally on the detailed particulars of real lives at the ground level of society. Throughout this book, I’ll highlight some recent studies that reﬂect this latter approach to understanding social life, in an attempt to “keep humanity in focus” during our broader discussion of social science practice. Statistics suggest that, in the United States, unwed mothers and their children, particularly those who are poor, will face a host of problems in the years to come. Both the child and the mother will likely struggle and suffer. The children are less likely to do well in school and in later life, and the mothers will probably have to struggle in low-paying jobs or live on welfare. The trend toward births out of wedlock has increased dramatically in recent decades, especially among the poor. As a reaction to these problems, the Bush administration launched a Healthy Marriage Initiative in 2005 aimed at encouraging childbearing couples to marry. Voices for and against the program have been raised with vigor. In their book Promises I Can Keep, Kathryn Edin and Maria Kefalas raise a question that might have been asked prior to the creation of a solution to the perceived problem:“Why do poor women bear children outside of wedlock?”The two social scientists spent ﬁve years speaking one-on-one with young women who had had children out of wedlock. Some of the things they learned dramatically contradicted various widespread images of unwed mothers. For instance, whereas many people have bemoaned the abandonment of marriage among the poor, the

as competing choices, a good social researcher learns each of the orientations they represent. This is what I mean by the “dialectics” of social research: There is a fruitful tension between the complementary concepts I’m about to describe.

Idiographic and Nomothetic Explanation All of us go through life explaining things. We do it every day. You explain why you did poorly or well on an exam, why your favorite team is winning or

women interviewed tended to speak highly of the institution, indicating they hoped to be married one day. Further, many were only willing to settle down with someone trustworthy and stable—better to remain unmarried than to enter a marriage that will end in disaster. At the same time, these young women felt strongly that their ultimate worth as women centered on their bearing children. Most felt it was preferable to be an unmarried mother than to be a childless woman, the real tragedy in their eyes. This view of marriage may differ greatly from your own. As we have seen, assumptions about “what’s real” are often contradicted by actual observations; this is crucial to understanding “what will work” to address social issues.

Promises I Can Keep: Why Poor Women Put Motherhood Before Marriage by Kathryn Edin and Maria Kefalas. © 2005 Regents of the University of California. Published by the University of California Press. Photograph © Michael Smyth

losing, why you may be having trouble getting good dates or a decent job. In our everyday explanations, we engage in two distinct forms of causal reasoning, though we do not ordinarily distinguish them. Sometimes we attempt to explain a single situation in idiosyncratic detail. Thus, for example, you may have done poorly on an exam because (1) you forgot there was an exam that day, (2) it was in your worst subject, (3) a trafﬁc jam made you late for class, (4) your roommate kept you up the night before the exam by playing loud music, (5) the police kept you until dawn demanding to know what you had done with your roommate’s stereo—

Some Dialectics of Social Research and what you had done with your roommate, for that matter—and (6) a wild band of coyotes ate your textbook. Given all these circ*mstances, it’s no wonder you did poorly. This type of causal reasoning is called an idiographic explanation. Idio- in this context means unique, separate, peculiar, or distinct, as in the word idiosyncrasy. When we have completed an idiographic explanation, we feel that we fully understand the causes of what happened in this particular instance. At the same time, the scope of our explanation is limited to the single case at hand. Although parts of the idiographic explanation might apply to other situations, our intention is to explain one case fully. Now consider a different kind of explanation. (1) Every time you study with a group, you do better on the exam than if you had studied alone. (2) Your favorite team does better at home than on the road. (3) Fraternity and sorority members get more dates than members of the biology club do. Notice that this type of explanation is more general, covering a wider range of experience or observation. It speaks implicitly of the relationship between variables: for example, (a) whether or not you study in a group and (b) how well you do on the exam. This type of explanation—labeled nomothetic —seeks to explain a class of situations or events rather than a single one. Moreover, it seeks to explain “economically,” using only one or just a few explanatory factors. Finally, it settles for a partial rather than a full explanation. In each of these examples, you might qualify your causal statements with such words or phrases as on the whole, usually, or all else being equal. Thus, you usually do better on exams when you’ve studied in a group, but not always. Similarly, your team has won some games on the road and lost some at home. And the attractive head of the biology club may get lots of good dates, while the homely members of sororities and fraternities spend a lot of Saturday nights alone working crossword puzzles. The existence of such exceptions is the price we pay for a broader range of overall explanation. As I noted earlier, patterns are real and important even when they are not perfect. Both the idiographic and the nomothetic approaches to understanding can be useful in daily

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life. The nomothetic patterns you discover might offer a good guide for planning your study habits, for example, while the idiographic explanation might be more convincing to your parole ofﬁcer. (See “Idiographic and Nomothetic Reasoning in Everyday Life.”) By the same token, both idiographic and nomothetic reasoning are powerful tools for social research. For example, A. Libin and J. Cohen-Mansﬁeld (2000) contrast the way that the idiographic and nomothetic approaches are used in studying the elderly (gerontology). Some studies focus on the full experiences of individuals as they live their lives, whereas other studies look for statistical patterns describing the elderly in general. The authors conclude by suggesting ways to combine idiographic and nomothetic approaches in gerontology. Social scientists, then, can access two distinct kinds of explanation. Just as physicists treat light sometimes as a particle and other times as a wave, so social scientists can search for broad relationships today and probe the narrowly particular tomorrow. Both are good science, both are rewarding, and both can be fun.

Inductive and Deductive Theory Like idiographic and nomothetic forms of explanation, inductive and deductive thinking both play a role in our daily lives. They, too, represent an important variation within social research.

idiographic An approach to explanation in which we seek to exhaust the idiosyncratic causes of a particular condition or event. Imagine trying to list all the reasons why you chose to attend your particular college. Given all those reasons, it’s difﬁcult to imagine your making any other choice. nomothetic An approach to explanation in which we seek to identify a few causal factors that generally impact a class of conditions or events. Imagine the two or three key factors that determine which colleges students choose—proximity, reputation, and so forth.

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Idiographic and Nomothetic Reasoning in Everyday Life

he difference between idiographic and nomothetic explanations can be found in everyday life. Consider the following: Idiographic: “He’s like that because his father and mother kept giving him mixed signals. The fact that his family moved seven times by the time he was twelve years old didn’t help. Moreover, his older brother is exactly the same and probably served as a role model.” Nomothetic: “Teenage boys are like that.” In the idiographic mode, we have a seemingly complete explanation for the behavior of the one boy in question. In the nomothetic mode,

For example, there are two routes to the conclusion that you do better on exams if you study with others. On the one hand, you might ﬁnd yourself puzzling, halfway through your college career, why you do so well on exams sometimes but poorly at other times. You might list all the exams you’ve taken, noting how well you did on each. Then you might try to recall any circ*mstances shared by all the good exams and by all the poor ones. Did you do better on multiple-choice exams or essay exams? Morning exams or afternoon exams? Exams in the natural sciences, the humanities, or the social sciences? Times when you studied alone or . . . SHAZAM! It occurs to you that you have almost always done best on exams when you studied with others. This mode of inquiry is known as induction. Induction, or inductive reasoning, moves from the particular to the general, from a set of speciﬁc observations to the discovery of a pattern that represents some degree of order among all the given events. Notice, incidentally, that your

induction The logical model in which general principles are developed from speciﬁc observations. Having noted that Jews and Catholics are more likely to vote Democratic than Protestants are, you might conclude that religious minorities in the United States are more afﬁliated with the Democratic party and then your task is to explain why. This would be an example of induction.

we have a simpler, more general, explanation, which wouldn’t necessarily be true of all teenage boys but portrays a general pattern. Be warned that neither explanation is necessarily true. When these models are used in social research, other elements of the inquiry—such as how subjects were chosen, how measurements were made, and so forth—strengthen the validity of conclusions drawn.

discovery doesn’t necessarily tell you why the pattern exists—just that it does. There is a second and very different way that you might arrive at the same conclusion about studying for exams. Imagine approaching your ﬁrst set of exams in college. You wonder about the best ways to study—how much you should review the readings, how much you should focus on your class notes. You learn that some students prepare by rewriting their notes in an orderly fashion. Then you consider whether you should study at a measured pace or else pull an all-nighter just before the exam. Among these kinds of musings, you might ask whether you should get together with other students in the class or just study on your own. You could evaluate the pros and cons of both options. Studying with others might not be as efﬁcient, because a lot of time might be spent on things you already understand. On the other hand, you can understand something better when you’ve explained it to someone else. And other students might understand parts of the course that you haven’t gotten yet. Several minds can reveal perspectives that might have escaped you. Also, your commitment to study with others makes it more likely that you’ll study rather than watch the special Brady Bunch retrospective. In this fashion, you might add up the pros and the cons and conclude, logically, that you’d beneﬁt from studying with others. It seems reasonable to you, the way it seems reasonable that you’ll do better if you study rather than not. Sometimes, we

Some Dialectics of Social Research say things like this are true “in theory.” To complete the process, we test whether they are true in practice. For a complete test, you might study alone for half your exams and study with others for the other exams. This procedure would test your logical reasoning. This second mode of inquiry, known as deduction or deductive reasoning, moves from the general to the speciﬁc. It moves from (1) a pattern that might be logically or theoretically expected to (2) observations that test whether the expected pattern actually occurs. Notice that deduction begins with “why” and moves to “whether,” whereas induction moves in the opposite direction. As you’ll see later in this book, these two very different approaches both serve as valid avenues for science. Each approach can stimulate the research process, prompting the researcher to take on speciﬁc questions and framing the manner in which they are addressed. Moreover, you’ll see how induction and deduction work together to provide ever more powerful and complete understandings. Figure 1-6 shows how these two approaches interact in the practice of social research. Notice, by the way, that the distinction between deductive and inductive reasoning is not necessarily linked to the distinction between nomothetic and idiographic modes of explanation. These four characterizations represent four possibilities, in everyday life as much as in social research. For example, idiographically and deductively, you might prepare for a particular date by taking into account everything you know about the person you’re dating, trying to anticipate logically how you can prepare—what type of clothing, behavior, hairstyle, oral hygiene, and so forth will likely produce a successful date. Or, idiographically and inductively, you might try to ﬁgure out what it was exactly that caused your date to call 911. A nomothetic, deductive approach arises when you coach others on your “rules of dating,” when you wisely explain why their dates will be impressed to hear them expound on the dangers of satanic messages concealed in rock and roll lyrics. When you later review your life and wonder why you didn’t date more musicians, you might engage in nomothetic induction.

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Image not available due to copyright restrictions

We’ll return to induction and deduction in Chapter 2. Let’s turn now to a third broad distinction that generates rich variations in social research.

Qualitative and Quantitative Data The distinction between quantitative and qualitative data in social research is essentially the distinction between numerical and nonnumerical data. When we say someone is intelligent, we’ve made a qualitative assertion. A corresponding assertion about someone less fortunately endowed would be that he or she is “unintelligent.” When psychologists and others measure intelligence by IQ scores, they are attempting to quantify such qualitative assessments. For example, the psychologist might say that a person has an IQ of 120.

deduction The logical model in which speciﬁc expectations of hypotheses are developed on the basis of general principles. Starting from the general principle that all deans are meanies, you might anticipate that this one won’t let you change courses. This anticipation would be the result of deduction.

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Every observation is qualitative at the outset, whether it is our experience of someone’s intelligence, the location of a pointer on a measuring scale, or a check mark entered in a questionnaire. None of these things is inherently numerical or quantitative, but converting them to a numerical form is sometimes useful. (Chapter 14 of this book will deal speciﬁcally with the quantiﬁcation of data.) Quantiﬁcation often makes our observations more explicit. It also can make it easier to aggregate, compare, and summarize data. Further, it opens up the possibility of statistical analyses, ranging from simple averages to complex formulas and mathematical models. Quantitative data, then, offer the advantages that numbers have over words as measures of some quality. On the other hand, they also carry the disadvantages that numbers have, including a potential loss in richness of meaning. For example, a social researcher might want to know whether college students aged 18–22 tend to date people older or younger than themselves. A quantitative answer to this question seems easily attained. The researcher asks a given number of college students how old each of their dates has been, calculates an average, and compares it with the age of the subject. Case closed. Or is it? Although “age” here represents the number of years people have been alive, sometimes people use the term differently; perhaps for some “age” really means “maturity.” You may date people who are younger than you but who act more maturely than others of their age and thus represent the same “age” as you. Or someone might see “age” as how young or old your dates look or maybe the degree of variation in their life experiences and worldliness. These latter meanings would be lost in the quantitative calculation of average age. Qualitative data, in short, can be richer in meaning than quantiﬁed data. This is implicit in the cliché, “He is older than his years.” The poetic meaning of this expression would be lost in attempts to specify how much older. On the other hand, qualitative data bring the disadvantages of purely verbal descriptions. For

example, the richness of meaning I’ve mentioned is partly a function of ambiguity. If the expression “older than his years” meant something to you when you read it, that meaning came from your own experiences, from people you have known who might ﬁt the description of being “older than their years” or perhaps the times you have heard others use that expression. Two things are certain: (1) You and I probably don’t mean exactly the same thing, and (2) you don’t know exactly what I mean, and vice versa. I have a friend, Ray Zhang, who was responsible for communications at the 1989 freedom demonstrations in Tiananmen Square, Beijing. Following the Army clampdown, Ray ﬂed south, was arrested, and was then released with orders to return to Beijing. Instead, he escaped from China and made his way to Paris. Eventually he came to the United States, where he resumed the graduate studies he had been forced to abandon in ﬂeeing his homeland. I have seen him deal with the difﬁculties of getting enrolled in school without any transcripts from China, of studying in a foreign language, of meeting his ﬁnancial needs—all on his own, thousands of miles from his family. Ray still speaks of one day returning to China to build a system of democracy. Ray strikes me as someone “older than his years.” You probably agree. The additional detail in my qualitative description, while it ﬂeshes out the meaning of the phrase, still does not equip us to say how much older or even to compare two people in these terms without the risk of disagreeing as to which one is more “worldly.” It might be possible to quantify this concept, however. For example, we might establish a list of life experiences that would contribute to what we mean by worldliness, for example: Getting married Getting divorced Having a parent die Seeing a murder committed Being arrested Being exiled

Some Dialectics of Social Research Being ﬁred from a job Running away with the circus We might quantify people’s worldliness as the number of such experiences they’ve had: the more such experiences, the more worldly we’d say they were. If we thought of some experiences as more powerful than others, we could give those experiences more points. Once we had made our list and point system, scoring people and comparing their worldliness on a numerical scale would be straightforward. We would have no difﬁculty agreeing on who had more points than who. To quantify a nonnumerical concept like worldliness, then, we need to be explicit about what the concept means. By focusing speciﬁcally on what we’ll include in our measurement of the concept, however, we also exclude any other meanings. Inevitably, then, we face a trade-off: Any explicated, quantitative measure will be less rich in meaning than the corresponding qualitative description. What a dilemma! Which approach should we choose? Which is better? Which is more appropriate to social research? The good news is that we don’t need to choose. In fact, we shouldn’t. Both qualitative and quantitative methods are useful and legitimate in social research. Some research situations and topics are amenable to qualitative examination, others to quantiﬁcation. Although researchers may use both, these two approaches call for different skills and procedures. As a result, you may ﬁnd that you feel more comfortable with—and become more adept in— one or the other. You will be a stronger researcher, however, to the extent that you can use both approaches effectively. Certainly, all researchers, whatever their personal inclinations, should recognize the legitimacy of both. You may have noticed that the qualitative approach seems more aligned with idiographic explanations, while nomothetic explanations are more easily achieved through quantiﬁcation. Although this is true, these relationships are not absolute. Moreover, both approaches present considerable “gray area.” Recognizing the distinc-

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tion between qualitative and quantitative research doesn’t mean that you must identify your research activities with one to the exclusion of the other. A complete understanding of a topic often requires both techniques. The contributions of these two approaches are widely recognized today. For example, when Stuart J. H. Biddle and his colleagues (2001) at the University of Wales set out to review the status of research in the ﬁeld of sport and exercise psychology, they were careful to examine the uses of both quantitative and qualitative techniques, drawing attention to those they felt were underused. The apparent conﬂict btween these two fundamental approaches has been neatly summarized by Paul Thompson (2004: 238–39): Only a few sociologists would openly deny the logic of combining the strengths of both quantitative and qualitative methods in social research. . . . In practice, however, despite such wider methodological aspirations in principle, social researchers have regrettably become increasingly divided into two camps, many of whose members know little of each other even if they are not explicitly hostile. In reviewing the frequent disputes over the superiority of qualitative or quantitative methods, Anthony Onwuegbuzie and Nancy Leech (2005) suggest that the two approaches have more similarities than differences, and they urge that social research is strengthened by the use of both. My intention in this book is to focus on the complementarity of these two approaches rather than on any apparent competition between them.

Pure and Applied Research From the beginning, social scientists have shown two distinct motivations: understanding and application. On the one hand, they are fascinated by the nature of human social life and are driven to explain it, to make sense out of apparent chaos. Pure research in all scientiﬁc ﬁelds is sometimes justiﬁed in terms of gaining “knowledge for knowledge’s sake.”

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At the same time, perhaps inspired by their subject matter, social scientists are committed to having what they learn make a difference, to seeing their knowledge of society put into action. Sometimes they focus on making things better. When I study prejudice, for example, I’d like what I discover to result in a more tolerant society. This is no different from the AIDS researcher trying to defeat that disease. In Chapter 12, we’ll focus on a special kind of applied research called evaluation research. For some social scientists, professional activities are intimately interwoven with the intention of creating a more humane society. Today, there is no better role model than the Egyptian sociologist Saad Eddin Ibrahim. Having addressed a great many social issues, Ibrahim has focused most recently on the problems of modern Arab societies in general and Egypt in particular. After years of researching and writing on the edge of political tolerance, Ibrahim crossed the line in 2000. Following the publication of one of my articles on Arab presidents grooming their sons to succeed them in the North Korean tradition of the late Kim Il Sung, the old guard seemed to have gotten a green light to come after me. The day after the article appeared on Cairo newsstands—June 30, 2000—I was arrested. (2003: 71)

Ibrahim provides a good example of how social scientists deal with something like imprisonment, which is, after all, an all-too-common part of modern social life. In those initial 45 days, my human contacts in prison were limited to prison wardens and guards. I had little opportunity to do as much sociological research on the prison community as I would have liked. That would have to wait for the second and third rounds of my imprisonment which followed in 2001 and 2002. (2003: 69)

One of the charges brought against Ibrahim was Article 80D of the penal code, which prohib-

its “spreading false rumors and tarnishing Egypt’s image abroad.” A more serious charge was that he had accepted ﬁnancial contributions from abroad without government permission, a violation of Military Order No. 4 of 1992. As Ibrahim was to learn, his research institute’s acceptance of research grants—usually a valued achievement—was regarded as a federal crime in his case. As Ibrahim observes, Being an activist sociologist in a Third World country is tremendously challenging. While some elements of the work are gratifying, it is more often permeated with agony. One honestly never knows when one is breaking a law, violating a military order or simply stepping over an invisible red line. (2003: 70)

Eventually, because of his own efforts and the international uproar produced by his arrest and imprisonment, Ibrahim was given a new trial and was ﬁnally released from prison on his 64th birthday: December 3, 2002. (You can learn more about Ibrahim’s experience at the link listed on this book’s website: http://www.cengage.com/ sociology/babbie.) Social researchers put their research into practice in many mundane ways as well. Experiments and surveys, for example, can be used in marketing products. In-depth interviewing techniques can be especially useful in social work encounters. Chapter 12 of this book deals with evaluation research, by which social scientists determine the effectiveness of social interventions. Sometimes, seemingly mundane research efforts can powerfully affect people’s lives. Imagine working alongside Crystal Eastman, an applied sociologist and settlement worker active in the Pittsburgh area in the early twentieth century: We got permission to use these [coroner’s records] and made a record of every industrial fatality reported to the coroner during the twelve months from July 1906 to July 1907, taking down on a separate card for each case, the name and address of the man killed, his

The Research Proposal age, occupation and conjugal condition, the name of his employer, the circ*mstances of the accident, the names of important witnesses, and the verdict. The plan was to learn from the evidence in the coroner’s record, how each accident happened, and to learn from visiting family what happened after the accident, [for example,] how great a ﬁnancial loss was suffered by the family of the workman killed, how much of this was made up by compensation received from the employer, and how the family was affected in its economic life by the accident. When we had done this with the fatalities, we followed the same course with the records of three months’ industrial injuries which we secured from the hospitals. (Eastman 1910: 789; quoted in Lengermann and Niebrugge-Brantley 2002: 13)

As a result of this and similar studies, U.S. workers now enjoy the protections of worker’s compensation insurance. As with each of the other dialectics just discussed, some social scientists are more inclined toward pure research, others toward application. Ultimately, both orientations are valid and vital elements in social research as a whole. In dealing with the basics of social research, whether pure or applied, one of the intentions of this book is to draw attention to the ways in which such research is used to make a difference. These, then, are some of the foundations of social research. I hope this discussion has helped to show how social science is anything but routine or boring. At its best, it is a vibrant, exciting, and important activity. All we need is an open mind and a sense of adventure.

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answer them. Often, such proposals are created for the purpose of getting the resources needed to conduct the research envisioned. One way to learn the topics of this course is to write a research proposal based on what you have learned. Even if you will not actually conduct a major research project, you can lay out a plan for doing so. Your instructor may use this as a course requirement, but even if that’s not the case, you can use the “Proposing Social Research” exercise at the end of each chapter to test your mastery of the chapter. There is a computer program, SAGrader, that is designed to assist you in writing exercises such as this one. It will accept a draft submission and critique it, pointing to elements that are missing, for example. You can learn more about SAGrader at the website listed at http://www.cengage.com/ sociology/babbie. There are many organizational structures for research proposals, and I’ve created a fairly typical one for you to use with this book. I’ve presented the proposal outline as follows, indicating which chapters in the book deal most directly with each topic. Introduction (Chapter 1) Review of the Literature (Chapters 2, 17; Appendix A) Specifying the Problem/Question/Topic (Chapters 5, 6, 12) Research Design (Chapter 4) Data-Collection Method (Chapters 4, 8, 9, 10, 11) Selection of Subjects (Chapter 7) Ethical Issues (Chapter 3) Data Analysis (Chapters 13, 14, 15, 16) Bibliography (Chapter 17; Appendix A)

The Research Proposal I conclude this chapter by introducing a feature that will run throughout the book: the preparation of a research proposal. Most organized research begins with a description of what is planned in the project: what questions it will raise and how it will

I’ll have more to say about each of these topics as we move through the book, beginning with this chapter’s “Proposing Social Research” exercise. Chapter 4 will have an extended section on the research proposal, and Chapter 17 will give you an opportunity to pull together all the parts of the proposal into a coherent whole.

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Chapter 1: Human Inquiry and Science

MAIN POINTS

•

Introduction

•

The subject of this book is how we ﬁnd out about social reality.

Looking for Reality

• • •

•

Inquiry is a natural human activity. Much of ordinary human inquiry seeks to explain events and predict future events. When we understand through direct experience, we make observations and seek patterns of regularities in what we observe. Much of what we know, we know by agreement rather than by experience. In particular, two important sources of agreed-on knowledge are tradition and authority. However, these useful sources of knowledge can also lead us astray. Science seeks to protect against the mistakes we make in day-to-day inquiry. Whereas we often observe inaccurately, researchers seek to avoid such errors by making observation a careful and deliberate activity. We sometimes jump to general conclusions on the basis of only a few observations, so scientists seek to avoid overgeneralization. They do this by committing themselves to a sufﬁcient number of observations and by replicating studies. In everyday life we sometimes reason illogically. Researchers seek to avoid illogical reasoning by being as careful and deliberate in their reasoning as in their observations. Moreover, the public nature of science means that others are always there to challenge faulty reasoning. Three views of “reality” are the premodern, modern, and postmodern views. In the postmodern view, there is no “objective” reality independent of our subjective experiences. Different philosophical views suggest a range of possibilities for scientiﬁc research.

The Foundations of Social Science

• • • •

Social theory attempts to discuss and explain what is, not what should be. Theory should not be confused with philosophy or belief. Social science looks for regularities in social life. Social scientists are interested in explaining human aggregates, not individuals. Theories are written in the language of variables.

•

A variable is a logical set of attributes. An attribute is a characteristic. Gender, for example, is a variable made up of the attributes male and female. In causal explanation, the presumed cause is the independent variable, and the affected variable is the dependent variable.

The Purposes of Social Research

• •

Three major purposes of social research are exploration, description, and explanation. Studies may aim to serve more than one of these purposes.

The Ethics of Human Inquiry

•

It is important to recognize from start that ethical issues, particularly with reference to protecting subjects, may rule out certain research procedures and/or require certain elements in the research design.

Some Dialectics of Social Science

• •

Whereas idiographic explanations present speciﬁc cases fully, nomothetic explanations present a generalized understanding of many cases. Inductive theories reason from speciﬁc observations to general patterns. Deductive theories start from general statements and predict speciﬁc observations. Quantitative data are numerical; qualitative data are not. Both types of data are useful for different research purposes. Both pure and applied research are valid and vital parts of the social science enterprise.

The Research Proposal

• •

Research projects often begin with the preparation of a research proposal, describing the purpose and methods of the proposed study. In this book, each chapter will conclude with an exercise through which you can prepare part of a research proposal, thereby testing your mastery of the topics covered.

KEY TERMS The following terms are deﬁned in context in the chapter and at the bottom of the page where the term is introduced, as well as in the comprehensive glossary at the back of the book.

Online Study Resources agreement reality attributes deduction dependent variable epistemology idiographic independent variable

induction methodology nomothetic replication theory variables

PROPOSING SOCIAL RESEARCH: INTRODUCTION This ﬁrst chapter has given you an overview of some of the basic variations in social research, many of which can be useful in writing the introduction of your research proposal. For this assignment, you should ﬁrst identify a topic or question you might like to explore in a research project. Perhaps you would like to explore some topic relating to race, gender, or social class. Perhaps there is some aspect of college life that you think needs study. Once you have a research topic in mind, this chapter will offer some ideas on how the research might be organized. This is only a overview of the project and should take two to four paragraphs. It will work best if you can select a topic which you’ll use in each of the chapters of the book, as you address different aspects of the research process. Here are some examples of research questions to illustrate the kind of focus your project might take.

• • • • • • • •

Do women earn less money than men and, if so, why? What distinguishes juvenile gangs of different ethnic groups? Which academic departments at your college offer the broadest degree of liberal arts training? Is it true, as some suggest, that the United States was established as a “Christian nation”? Are American military actions in the Middle East reducing the threat of terrorist attacks or increasing those threats? What are the major functions of the American family and how have those been changing over time? Are ofﬁcial attempts to control illegal drug use succeeding or failing? Do undocumented immigrants overall represent a net economic cost or beneﬁt to the United States?

Notice that you probably hear questions like these discussed frequently, both in your own interactions

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and in the mass media. Most of those discussions are probably mostly based in opinions. Your opportunity in this course is to see how you might pursue such questions as a researcher, dealing with logic and facts in place of opinions.

REVIEW QUESTIONS AND EXERCISES 1. Review the common errors of human inquiry discussed in this chapter. Find a magazine or newspaper article, or perhaps a letter to the editor, that illustrates one of these errors. Discuss how a scientist would avoid it. 2. List ﬁve social variables and the attributes they comprise. 3. Go to one of the following websites, listed at www.cengage.com/sociology/babbie, and ﬁnd examples of both qualitative and quantitative data. a.

UN High Commissioner for Refugees

b. U.S. Centers for Disease Control and Prevention c.

National Library of Australia

4. At InfoTrac College Edition, search for “postmodernism.” Write a short report discussing the various ﬁelds or disciplines to which it has been applied. Give examples.

SPSS EXERCISES See the booklet that accompanies your text for exercises using SPSS (Statistical Package for the Social Sciences). There are exercises offered for each chapter, and you’ll also ﬁnd a detailed primer on using SPSS.

Online Study Resources If your book came with an access code card, visit www.cengage.com/login to register. To purchase access, please visit www.ichapters.com. 1. Before you do your ﬁnal review of the chapter, take the CengageNOW pretest to help identify the areas on which you should concentrate. You’ll ﬁnd information on this online tool, as well as instructions on how to access all of its great resources, in the front of the book.

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Chapter 1: Human Inquiry and Science

2. As you review, take advantage of the CengageNOW personalized study plan, based on your quiz results. Use this study plan with its interactive exercises and other resources to master the material. 3. When you’re ﬁnished with your review, take the posttest to conﬁrm that you’re ready to move on to the next chapter.

WEBSITE FOR THE PRACTICE OF SOCIAL RESEARCH 12TH EDITION Go to your book’s website at www.cengage.com/ sociology/babbie for tools to aid you in studying for your exams. You’ll ﬁnd Tutorial Quizzes with

feedback, Internet Exercises, Flash Cards, Glossaries, and Essay Quizzes, as well as InfoTrac College Edition search terms, suggestions for additional reading, Web Links, and primers for using data-analysis software such as SPSS.

CHAPTER TWO

Paradigms, Theory, and Social Research CHAPTER OVERVIEW

Social science inquiry is an interplay of theory and research, logic and observation, induction and deduction—and of the fundamental frames of reference known as paradigms.

Introduction Some Social Science Paradigms Macrotheory and Microtheory Early Positivism Social Darwinism Conﬂict Paradigm Symbolic Interactionism Ethnomethodology Structural Functionalism Feminist Paradigms Critical Race Theory Rational Objectivity Reconsidered Elements of Social Theory Two Logical Systems Revisited The Traditional Model of Science

Deductive and Inductive Reasoning: A Case Illustration A Graphic Contrast Deductive Theory Construction Getting Started Constructing Your Theory An Example of Deductive Theory: Distributive Justice Inductive Theory Construction An Example of Inductive Theory: Why Do People Smoke Marijuana? The Links between Theory and Research Research Ethics and Theory

CengageNOW for Sociology Use this online tool to help you make the grade on your next exam. After reading this chapter, go to “Online Study Resources” at the end of the chapter for instructions on how to beneﬁt from CengageNOW.

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Chapter 2: Paradigms, Theory, and Social Research

Introduction Certain restaurants in the United States are fond of conducting political polls among their diners whenever an election is in the ofﬁng. Some take these polls very seriously because of their uncanny history of predicting winners. Some movie theaters have achieved similar success by offering popcorn in bags picturing either donkeys or elephants. Years ago, granaries in the Midwest offered farmers a chance to indicate their political preferences through the bags of grain they selected. Such idiosyncratic ways of determining trends, though interesting, all follow the same pattern over time: They work for a while, and then they fail. Moreover, we can’t predict when or why they will fail. These unusual polling techniques point to a signiﬁcant shortcoming of “research ﬁndings” that are based only on the observation of patterns. Unless we can offer logical explanations for such patterns, the regularities we’ve observed may be mere ﬂukes, chance occurrences. If you ﬂip coins long enough, you’ll get ten heads in a row. Scientists might adapt a street expression to describe this situation: “Patterns happen.” Logical explanations are what theories seek to provide. Theories function in three ways in research. First, they prevent our being taken in by ﬂukes. If we can’t explain why Ma’s Diner has so successfully predicted elections, we run the risk of supporting a ﬂuke. If we know why it has happened, we can anticipate whether or not it will work in the future. Second, theories make sense of observed patterns in a way that can suggest other possibilities. If we understand the reasons why broken homes produce more juvenile delinquency than intact homes do—lack of supervision, for example—we can take effective action, such as after-school youth programs. Finally, theories shape and direct research efforts, pointing toward likely discoveries through empirical observation. If you were looking for your

lost keys on a dark street, you could whip your ﬂashlight around randomly, hoping to chance upon the errant keys— or you could use your memory of where you had been and limit your search to more likely areas. Theories, by analogy, direct researchers’ ﬂashlights where they will most likely observe interesting patterns of social life. This is not to say that all social science research is tightly intertwined with social theory. Sometimes social scientists undertake investigations simply to discover the state of affairs, such as an evaluation of whether an innovative social program is working or a poll to determine which candidate is winning a political race. Similarly, descriptive ethnographies, such as anthropological accounts of preliterate societies, produce valuable information and insights in and of themselves. However, even studies such as these often go beyond pure description to ask “why.” Theory relates directly to “why” questions. This chapter explores some speciﬁc ways theory and research work hand in hand during the adventure of inquiry into social life. We’ll begin by looking at some fundamental frames of reference, called paradigms, that underlie social theories and inquiry. Whereas theories seek to explain, paradigms provide ways of looking. In and of themselves, paradigms don’t explain anything; however, they provide logical frameworks within which theories are created. As you’ll see in this chapter, theories and paradigms intertwine in the search for meaning in social life.

Some Social Science Paradigms There is usually more than one way to make sense of things. In daily life, for example, liberals and conservatives often explain the same phenomenon—teenagers using guns at school, for example—quite differently. So might the parents and teenagers themselves. But underlying these different explanations, or theories, are

Some Social Science Paradigms paradigms—the fundamental models or frames of reference we use to organize our observations and reasoning. Paradigms are often difﬁcult to recognize as such, because they are so implicit, assumed, taken for granted. They seem more like “the way things are” than like one possible point of view among many. Here’s an illustration of what I mean. Where do you stand on the issue of human rights? Do you feel that individual human beings are sacred? Are they “endowed by their creator with certain inalienable rights,” as asserted by the U.S. Declaration of Independence? Are there some things that no government should do to its citizens? Let’s get more concrete. In wartime, civilians are sometimes used as human shields to protect military targets. Sometimes they are impressed into slave labor or even used as mobile blood banks for military hospitals. How about organized programs of rape and murder in support of “ethnic cleansing”? Those of us who are horriﬁed and incensed by such practices probably ﬁnd it difﬁcult to see our individualistic paradigm as only one possible point of view among many. However, many cultures in today’s world regard the Western (and particularly U.S.) commitment to the sanctity of the individual as bizarre. Historically, it has decidedly been a minority viewpoint. Although many Asian countries, for example, now subscribe to some “rights” that belong to individuals, those are balanced against the “rights” of families, organizations, and the society at large. Criticized for violating human rights, Asian leaders often point to high crime rates and social disorganization in Western societies as the cost of what they see as our radical “cult of the individual.” I won’t try to change your point of view on individual human dignity, nor have I given up my own. It’s useful, however, to recognize that our views and feelings in this matter result from the paradigm we have been socialized into. The sanctity of the individual is not an objective fact of nature; it is a point of view, a paradigm. All of us operate within many such paradigms. A traditional Western view holds that the world you experience has an objective reality separate

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from your experience of it. As we saw in Chapter 1, however, the postmodern paradigm suggests that only the experience is real: The book in your hands right now is not real; only your experience of it is. Whether you think the book really exists or not reﬂects the paradigm you operate within. When we recognize that we are operating within a paradigm, two beneﬁts accrue. First, we can better understand the seemingly bizarre views and actions of others who are operating from a different paradigm. Second, at times we can proﬁt from stepping outside our paradigm. Suddenly we can see new ways of seeing and explaining things. We can’t do that as long as we mistake our paradigm for reality. Paradigms play a fundamental role in science, just as they do in daily life. Thomas Kuhn (1970) draws attention to the role of paradigms in the history of the natural sciences. Major scientiﬁc paradigms have included such fundamental viewpoints as Copernicus’s conception of the earth moving around the sun (instead of the reverse), Darwin’s theory of evolution, Newtonian mechanics, and Einstein’s relativity. Which scientiﬁc theories “make sense” depends on which paradigm scientists are maintaining. Although we sometimes think of science as developing gradually over time, marked by important discoveries and inventions, Kuhn says that scientiﬁc paradigms typically become entrenched, resisting substantial change. Thus, theories and research alike tend to follow a given fundamental direction. Eventually, however, as the shortcomings of a particular paradigm became obvious, a new one emerges and supplants the old. The seemingly natural view that the rest of the universe revolves around the earth, for example, compelled astronomers to devise ever more elaborate ways to account for the motions of heavenly bodies that they actually observed. Eventually this paradigm was supplanted by the view that the earth and other planets revolve around the sun. This was

paradigm A model or frame of reference through which to observe and understand.

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Chapter 2: Paradigms, Theory, and Social Research

nothing less than a revolutionary change in perspective, which fundamentally altered the direction of theory and research. Kuhn’s classic book on this subject is entitled, appropriately enough, The Structure of Scientiﬁc Revolutions. Social scientists have developed several paradigms for understanding social behavior. The fate of supplanted paradigms in the social sciences, however, has differed from what Kuhn observed in the natural sciences. Natural scientists generally believe that the succession from one paradigm to another represents progress from a false view to a true one. For example, no modern astronomer believes that the sun revolves around the earth. In the social sciences, on the other hand, theoretical paradigms may gain or lose popularity, but they are seldom discarded altogether. The paradigms of the social sciences offer a variety of views, each of which offers insights the others lack and ignores aspects of social life that the others reveal. Ultimately, paradigms are neither true nor false; as ways of looking, they are only more or less useful. Each of the paradigms we are about to examine offers a different way of looking at human social life. Each makes its own assumptions about the nature of social reality. As we’ll see, each can open up new understandings, suggest different kinds of theories, and inspire different kinds of research.

macrotheories include the struggle between economic classes in a society, international relations, or the interrelations among major institutions in society, such as government, religion, and family. Macrotheory deals with large, aggregate entities of society or even whole societies. (Note that some researchers prefer to limit the macrolevel to whole societies, using the term mesotheory for an intermediate level between macro and micro: studying organizations, communities, and perhaps social categories such as gender.) Some scholars have taken a more intimate view of social life. Microtheory deals with issues of social life at the level of individuals and small groups. Dating behavior, jury deliberations, and student–faculty interactions are apt subjects for a microtheoretical perspective. Such studies often come close to the realm of psychology, but whereas psychologists typically focus on what goes on inside humans, social scientists study what goes on between them. The basic distinction between macro- and microtheory cuts across the other paradigms we’ll examine. Some of them, such as symbolic interactionism and ethnomethodology, are often limited to the microlevel. Others, such as the conﬂict paradigm, can be pursued at either the micro- or the macrolevel.

Macrotheory and Microtheory

Early Positivism

Let’s begin with a difference concerning focus, a difference that stretches across many of the paradigms we’ll discuss. Some social theorists focus their attention on society at large, or at least on large portions of it. Topics of study for such

When the French philosopher Auguste Comte (1798–1857) coined the term sociologie in 1822, he launched an intellectual adventure that continues to unfold today. Most importantly, Comte identiﬁed society as a phenomenon that can be studied scientiﬁcally. (Initially, he wanted to label his enterprise social physics, but that term was taken over by another scholar.) Prior to Comte’s time, society simply was. To the extent that people recognized different kinds of societies or changes in society over time, religious paradigms generally predominated in explanations of such differences. People often saw the state of social affairs as a reﬂection of God’s will. Alternatively, people were challenged to create a “City of God” on earth to replace sin and godlessness.

macrotheory A theory aimed at understanding the “big picture” of institutions, whole societies, and the interactions among societies. Karl Marx’s examination of the class struggle is an example of macrotheory. microtheory A theory aimed at understanding social life at the intimate level of individuals and their interactions. Examining how the play behavior of girls differs from that of boys would be an example of microtheory.

Some Social Science Paradigms Comte separated his inquiry from religion. He felt that religious belief could be replaced with scientiﬁc study and objectivity. His “positive philosophy” postulated three stages of history. A theological stage predominated throughout the world until about 1300 C.E. During the next ﬁve hundred years, a metaphysical stage replaced God with philosophical ideas such as “nature” and “natural law.” Comte felt he was launching the third stage of history, in which science would replace religion and metaphysics by basing knowledge on observations through the ﬁve senses rather than on belief or logic alone. Comte felt that society could be observed and then explained logically and rationally and that sociology could be as scientiﬁc as biology or physics. In a sense, all social research descends from Comte. His view that society could be studied scientiﬁcally formed the foundation for subsequent development of the social sciences. In his optimism for the future, he coined the term positivism to describe this scientiﬁc approach, in contrast to what he regarded as negative elements in the Enlightenment. As we’ll see later in this discussion, positivism has been seriously challenged only in recent decades.

Social Darwinism Comte’s major work on his positivist philosophy was published between 1830 and 1842. One year after the publication of the ﬁrst volume in that series, a young British naturalist set sail on HMS Beagle, beginning a cruise that would profoundly affect the way we think of ourselves and our place in the world. In 1858, when Charles Darwin published On the Origin of Species, he set forth the idea of evolution through natural selection. Simply put, the theory states that as a species coped with its environment, those individuals most suited to success would be the most likely to survive long enough to reproduce. Those less well suited would perish. Over time the traits of the survivor would come to dominate the species. As later Darwinians put it,

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species evolved into different forms through the “survival of the ﬁttest.” As scholars began to study society analytically, it was perhaps inevitable that they would apply Darwin’s ideas to changes in the structure of human affairs. The journey from simple hunting-andgathering tribes to large, industrial civilizations was easily seen as the evolution of progressively “ﬁtter” forms of society. Among others, Herbert Spencer (1820–1903) concluded that society was getting better and better. Indeed, his native England had proﬁted greatly from the development of industrial capitalism, and Spencer favored a system of free competition, which he felt would insure continued progress and improvement. Spencer may even have coined the phrase “the survival of the ﬁttest.” He certainly believed that this principle was a primary force shaping the nature of society. Social Darwinism or social evolution was a popular view in Spencer’s time, although it was not universally accepted. This excerpt from a social science methods textbook published in 1950 illustrates the long-term popularity of the notion that things are getting better and better. The use of atomic energy as an explosive offers most interesting prospects in the civil as in the military ﬁeld. Atomic explosives may be used for transforming the landscape. They may be used for blasting great holes and trenches in the earth, which can be transformed into lakes and canals. In this way, it may become possible to produce lakes in the midst of deserts, and thus convert some of the worst places in the world into oases and fertile countries. It may also be possible to make the Arctic regions comfortable by providing immense and constant sources of heat. The North Pole might be converted into a holiday resort. (Gee 1950: 339 – 40)

positivism Introduced by August Comte, this philosophical system is grounded on the rational proof/ disproof of scientiﬁc assertions; assumes a knowable, objective reality.

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Chapter 2: Paradigms, Theory, and Social Research

Quite aside from the widespread disenchantment with nuclear power, contemporary concerns over global warming and the threat of rising sea levels illustrate a growing consciousness that “progress” is often a two-edged sword. Clearly, most of us operate today from a different paradigm.

Conﬂict Paradigm One of Spencer’s contemporaries took a sharply different view of the evolution of capitalism. Karl Marx (1818–1883) suggested that social behavior could best be seen as a process of conﬂict: the attempt to dominate others and to avoid being dominated. Marx focused primarily on the struggle among economic classes. Speciﬁcally, he examined the way capitalism produced the oppression of workers by the owners of industry. Marx’s interest in this topic did not end with analytical study; he was also ideologically committed to restructuring economic relations to end the oppression he observed. The contrast between the views set forth by Spencer and Marx indicates the inﬂuence of paradigms on research. These fundamental viewpoints shape the kinds of observations we are likely to make, the sorts of facts we seek to discover, and the conclusions we draw from those facts. Paradigms also help determine which concepts we see as relevant and important. Whereas economic classes were essential to Marx’s analysis, for example, Spencer was more interested in the relationship between individuals and society—particularly the amount of freedom individuals had to surrender for society to function. The conﬂict paradigm proved to be fruitful outside the realm of purely economic analyses. Georg Simmel (1858–1918) was especially interested in small-scale conﬂict, in contrast to the class struggle that interested Marx. Simmel noted, for example, that conﬂicts among members of a tightly knit group tended to be more intense than

conﬂict paradigm A paradigm that views human behavior as attempts to dominate others or avoid being dominated by others.

those among people who did not share feelings of belonging and intimacy. In a more recent application of the conﬂict paradigm, when Michel Chossudovsky’s (1997) analysis of the International Monetary Fund (IMF) and World Bank suggested that these two international organizations were increasing global poverty rather than eradicating it, he directed his attention to the competing interests involved in the process. In theory, the chief interest being served should be the poor people of the world or perhaps the impoverished, Third World nations. The researcher’s inquiry, however, identiﬁed many other interested parties who beneﬁted: the commercial lending institutions who made loans in conjunction with the IMF and World Bank, as well as multinational corporations seeking cheap labor and markets for their goods, for example. Chossudovsky concluded that the interests of the banks and corporations tended to take precedence over those of the poor people. Moreover, he found that many policies were weakening national economies in the Third World, as well as undermining democratic governments. Although the conﬂict paradigm often focuses on class, gender, and ethnic struggles, we could appropriately apply it whenever different groups have competing interests. For example, we could fruitfully apply it to understanding relations among different departments in an organization, fraternity and sorority rush weeks, or student–faculty– administrative relations, to name just a few.

Symbolic Interactionism In his overall focus, Georg Simmel differed from both Spencer and Marx. Whereas they were chieﬂy concerned with macrotheoretical issues—large institutions and whole societies in their evolution through the course of history—Simmel was more interested in how individuals interacted with one another. In other words, his thinking and research took a “micro” turn, thus calling attention to aspects of social reality that are invisible in Marx’s or Spencer’s theory. For example, he began by examining dyads (groups of two people) and triads (groups of three). Similarly, he wrote about “the web of group afﬁliations.”

Some Social Science Paradigms Simmel was one of the ﬁrst European sociologists to inﬂuence the development of U.S. sociology. His focus on the nature of interactions particularly inﬂuenced George Herbert Mead (1863–1931), Charles Horton Cooley (1864–1929), and others who took up the cause and developed it into a powerful paradigm for research. Cooley, for example, introduced the idea of the “primary group,” those intimate associates with whom we share a sense of belonging, such as our family and friends. Cooley also wrote of the “looking-glass self” we form by looking into the reactions of people around us. If everyone treats us as beautiful, for example, we conclude that we are. Notice how fundamentally the concepts and theoretical focus inspired by this paradigm differ from the society-level concerns of Spencer and Marx. Mead emphasized the importance of our human ability to “take the role of the other,” imagining how others feel and how they might behave in certain circ*mstances. As we gain an idea of how people in general see things, we develop a sense of what Mead called the “generalized other.” Mead also showed a special interest in the role of communications in human affairs. Most interactions, he felt, revolved around the process of individuals reaching common understanding through the use of language and other such systems, hence the term symbolic interactionism. This paradigm can lend insights into the nature of interactions in ordinary social life, but it can also help us understand unusual forms of interaction, as in the following case. Robert Emerson, Kerry Ferris, and Carol Gardner (1998) set out to understand the nature of “stalking.” Through interviews with numerous stalking victims, they came to identify different motivations among stalkers, stages in the development of a stalking scenario, how people can recognize if they are being stalked, and what they can do about it. Here’s one way you might apply the symbolic interactionism paradigm to an examination of your own life. The next time you meet someone new, pay attention to how you get to know each other. To begin, what assumptions do you make about the other person based merely on appearances, how

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he or she talks, and the circ*mstances under which you’ve met. (“What’s someone like you doing in a place like this?”) Then watch how your knowledge of each other unfolds through the process of interaction. Notice also any attempts you make to manage the image you are creating in the other person’s mind.

Ethnomethodology Whereas some social science paradigms emphasize the impact of social structure on human behavior— that is, the effect of norms, values, control agents, and so forth— other paradigms do not. Harold Garﬁnkel, a contemporary sociologist, claims that people are continually creating social structure through their actions and interactions—that they are, in fact, creating their realities. Thus, when you and your instructor meet to discuss your term paper, even though there are myriad expectations about how you both should act, your conversation will differ somewhat from any of those that have occurred before, and how you each act will somewhat modify your expectations in the future. That is, discussing your term paper will impact the interactions each of you have with other professors and students in the future. Given the tentativeness of reality in this view, Garﬁnkel suggests that people are continuously trying to make sense of the life they experience. In a sense, he suggests that everyone is acting like a social scientist, hence the term ethnomethodology, or “methodology of the people.” How would you go about learning about people’s expectations and how they make sense out of their world? One technique ethnomethodologists use is to break the rules, to violate people’s expectations. Thus, if you try to talk to me about your term paper but I keep talking about football, this might reveal the expectations you had for my behavior. We might also see how you make sense out of my

symbolic interactionism A paradigm that views human behavior as the creation of meaning through social interactions, with those meanings conditioning subsequent interactions.

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behavior. (“Maybe he’s using football as an analogy for understanding social systems theory.”) In another example of ethnomethodology, Johen Heritage and David Greatbatch (1992) examined the role of applause in British political speeches: How did the speakers evoke applause, and what function did it serve (for example, to complete a topic)? Research within the ethnomethodological paradigm has often focused on communications. There is no end to the opportunities you have for trying out the ethnomethodological paradigm. For instance, the next time you get on an elevator, don’t face front, watching the ﬂoor numbers whip by (that’s the norm, or expected behavior). Just stand quietly facing the rear. See how others react to this behavior. Just as important, notice how you feel about it. If you do this experiment a few times, you should begin to develop a feel for the ethnomethodological paradigm.* We’ll return to ethnomethodology in Chapter 10, when we discuss ﬁeld research. For now, let’s turn to a very different paradigm.

Structural Functionalism Structural functionalism, sometimes also known as social systems theory, has grown out of a notion introduced by Comte and Spencer: A social entity, such as an organization or a whole society, can be viewed as an organism. Like other organisms, a social system is made up of parts, each of which contributes to the functioning of the whole. By analogy, consider the human body. Each component—such as the heart, lungs, kidneys, skin, and brain—has a particular job to do. The body as a whole cannot survive unless each of these parts does its job, and none of the parts can survive except as a part of the whole body. Or consider an automobile. It is composed of the tires, the steering wheel, the gas tank, the spark plugs,

structural functionalism A paradigm that divides social phenomena into parts, each of which serves a function for the operation of the whole.

and so forth. Each of the parts serves a function for the whole; taken together, that system can get us across town. None of the individual parts would be very useful to us by itself, however. The view of society as a social system, then, looks for the “functions” served by its various components. Social scientists using the structural functional paradigm might note that the function of the police, for example, is to exercise social control—encouraging people to abide by the norms of society and bringing to justice those who do not. Notice, though, that the researchers could just as reasonably ask what functions criminals serve in society. Within the functionalist paradigm, we might say that criminals serve as job security for the police. In a related observation, Emile Durkheim (1858–1917) suggested that crimes and their punishment provide an opportunity to reafﬁrm society’s values. By catching and punishing thieves, we reafﬁrm our collective respect for private property. To get a sense of the structural functional paradigm, suppose you were interested in explaining how your college or university works. You might thumb through the institution’s catalog and begin assembling a list of the administrators and support staff (such as the president, deans, registrar, campus security staff, maintenance personnel). Then you might ﬁgure out what each of them does and relate their roles and activities to the chief functions of your college or university, such as teaching or research. This way of looking at an institution of higher learning would clearly suggest a different line of inquiry than, say, a conﬂict paradigm, which might emphasize the clash of interests between people who have power in the institution and those who don’t. People often discuss “functions” in everyday conversation. Typically, however, the alleged functions are seldom tested empirically. Some people argue, for example, that welfare, intended to help

*I am grateful to my colleague, Bernard McGrane, for this experiment. Barney also has his students eat dinner with their hands, watch TV without turning it on, and engage in other strangely enlightening behavior (McGrane 1994).

Some Social Science Paradigms the poor, actually harms them in a variety of ways. It is sometimes alleged that welfare creates a deviant, violent subculture in society, at odds with the mainstream. From this viewpoint, welfare programs actually result in increased crime rates. Lance Hannon and James Defronzo (1998) decided to test this last assertion. Working with data drawn from 406 urban counties in the United States, they examined the relationship between welfare payments and crime rates. Contrary to the beliefs of some, their data indicated that higher welfare payments were associated with lower crime rates. In other words, welfare programs have the function of decreasing rather than increasing lawlessness. In applying the functionalist paradigm to everyday life, people sometimes make the mistake of thinking that “functionality,” stability, and integration are necessarily good, or that the functionalist paradigm makes that assumption. However, when social researchers look for the functions served by poverty, racial discrimination, or the oppression of women, they are not justifying them. Just the opposite: They seek to understand the functions such things play in the larger society, as a way of understanding why they persist and how they could be eliminated.

Feminist Paradigms When Ralph Linton concluded his anthropological classic, The Study of Man (1937: 490), speaking of “a store of knowledge that promises to give man a better life than any he has known,” no one complained that he had left out women. Linton was using the linguistic conventions of his time; he implicitly included women in all his references to men. Or did he? When feminists ﬁrst began questioning the use of masculine pronouns and nouns whenever gender was ambiguous, their concerns were often viewed as petty, even silly. At most, many felt the issue was one of women having their feelings hurt, their egos bruised. But be honest: When you read Linton’s words, what did you picture? An amorphous, genderless human being, a hermaphrodite at once male and female, or a male persona?

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In a similar way, researchers looking at the social world from a feminist paradigm have called attention to aspects of social life that other paradigms do not reveal. In part, feminist theory and research have focused on gender differences and how they relate to the rest of social organization. These lines of inquiry have drawn attention to the oppression of women in many societies, which in turn has shed light on oppression generally. Feminist paradigms not only reveal the treatment of women or the experience of oppression but often point to limitations in how other aspects of social life are examined and understood. Thus, feminist perspectives are often related to a concern for the environment, for example. As Greta Gard suggests, The way in which women and nature have been conceptualized historically in Western intellectual tradition has resulted in devaluing whatever is associated with women, emotion, animals, nature, and the body, while simultaneously elevating in value those things associated with men, reason, humans, culture, and the mind. One task of ecofeminism has been to expose these dualisms and the ways in which feminizing nature and naturalizing or animalizing women has served as justiﬁcation for the domination of women, animals and the earth. (1993: 5; quoted in Rynbrandt and Deegan 2002: 60)

Feminist paradigms have also challenged the prevailing notions concerning consensus in society. Most descriptions of the predominant beliefs, values, and norms of a society are written by people representing only portions of society. In the United States, for example, such analyses have typically been written by middle-class white men—not surprisingly, they have written about the beliefs, values, and norms they themselves share. Though George Herbert Mead spoke of the

feminist paradigms Paradigms that (1) view and understand society through the experiences of women and/or (2) examine the generally deprived status of women in society.

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“generalized other” that each of us becomes aware of and can “take the role of,” feminist paradigms question whether such a generalized other even exists. Further, whereas Mead used the example of learning to play baseball to illustrate how we learn about the generalized other, Janet Lever’s research suggests that understanding the experience of boys may tell us little about girls. Girls’ play and games are very different. They are mostly spontaneous, imaginative, and free of structure or rules. Turn-taking activities like jumprope may be played without setting explicit goals. Girls have far less experience with interpersonal competition. The style of their competition is indirect, rather than face to face, individual rather than team afﬁliated. Leadership roles are either missing or randomly ﬁlled. (Lever 1986: 86)

Social researchers’ growing recognition of the general intellectual differences between men and women led the psychologist Mary Field Belenky and her colleagues to speak of Women’s Ways of Knowing (1986). In-depth interviews with 45 women led the researchers to distinguish ﬁve perspectives on knowing that should challenge the view of inquiry as obvious and straightforward: Silence: Some women, especially early in life, feel themselves isolated from the world of knowledge, their lives largely determined by external authorities. Received knowledge: From this perspective, women feel themselves capable of taking in and holding knowledge originating with external authorities. Subjective knowledge: This perspective opens up the possibility of personal, subjective knowledge, including intuition. Procedural knowledge: Some women feel they have fully learned the ways of gaining knowledge through objective procedures. Constructed knowledge: The authors describe this perspective as “a position in which women view all knowledge as contextual, experience themselves as creators of knowledge, and value

both subjective and objective strategies for knowing” (Belenky et al. 1986: 15). “Constructed knowledge” is particularly interesting in the context of paradigms. The positivistic paradigm of Comte would have a place neither for “subjective knowledge” nor for the idea that truth might vary according to its context. The ethnomethodological paradigm, on the other hand, would accommodate these ideas. Feminist standpoint theory is a term often used in reference to the fact that women have knowledge about their status and experience that is not available to men. Introduced by Nancy Hartsock (1983), this viewpoint has evolved over time. For example, scholars have come to recognize that there is no single female experience, that different kinds of women (varying by wealth, ethnicity, or age, for example) have very different experiences of life in society, all the while sharing some things in common because of their gender. This sensitivity to variations in the female experience is also a main element in what is referred to as third-wave feminism, which began in the 1990s. To try out feminist paradigms, you might want to explore whether discrimination against women exists at your college or university. Are the top administrative positions held equally by men and women? How about secretarial and clerical positions? Are men’s and women’s sports supported equally? Read through the ofﬁcial history of your school; is it a history that includes men and women equally? (If you attend an all-male or all-female school, of course, some of these questions won’t apply.) As we just saw, feminist paradigms reﬂect both a concern for the unequal treatment of women but also an epistemological recognition that men and women overall perceive and understand society differently. Social theories created solely by men, which has been the norm, run the risk of an unrecognized bias. A similar case can be made for theories created almost exclusively by white people.

Critical Race Theory The roots of critical race theory are generally associated with the civil rights movement of the mid1950s and race-related legislation of the 1960s. By

Some Social Science Paradigms the mid-1970s, with fears that the strides toward equality were beginning to bog down, civil rights activists and social scientists began the codiﬁcation of a paradigm based on race awareness and a commitment to racial justice. This was not the ﬁrst time sociologists paid attention to the status of nonwhites in U.S. society. Perhaps the best known African American sociologist in the history of the discipline was W. E. B. DuBois, who published The Souls of Black Folk in 1903. Among other things, DuBois pointed out that African Americans lived their lives through a “dual consciousness”: as Americans and as black people. By contrast, white Americans seldom reﬂect on being white. If you are American, white is simply assumed. If you are not white, you are seen and feel like the exception. So imagine the difference between an African American sociologist and a white sociologist creating a theory of social identity. Their theories of identity would likely differ in some fundamental ways, even if they were not limiting their analyses to their own race. Much of the contemporary scholarship in critical race theory has to do with the role of race in politics and government, often undertaken by legal scholars as well as social scientists. Thus, for example, Derrick Bell (1980) critiqued the Supreme Court’s landmark Brown vs. Board of Education decision, which struck down the “separate but equal” system of school segregation. He suggested that the Court was motivated by the economic and political interests of the white majority, not by educational equality for African American students. In his analysis, he introduced the concept of interest convergence, suggesting that laws will only be changed to beneﬁt African Americans if and when those changes are seen to further the interests of whites. Richard Delgado (2002) provides an excellent overview of how Bell’s reasoning has been pursued by subsequent critical race theory scholars. As a general rule, whenever you ﬁnd the word critical in the name of a paradigm or theory, it will likely refer to a nontraditional view, one that may be at odds with the prevailing paradigms of an academic discipline and also at odds with the mainstream structure of society.

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Rational Objectivity Reconsidered We began this discussion of paradigms with Comte’s assertion that society can be studied rationally and objectively. Since his time, the growth of science and technology, together with the relative decline of superstition, have put rationality more and more at the center of social life. As fundamental as rationality is to most of us, however, some contemporary scholars have raised questions about it. For example, positivistic social scientists have sometimes erred in assuming that humans always act rationally. I’m sure your own experience offers ample evidence to the contrary. Yet many modern economic models fundamentally assume that people will make rational choices in the economic sector: They will choose the highest-paying job, pay the lowest price, and so forth. This assumption ignores the power of tradition, loyalty, image, and other factors that compete with reason and calculation in determining human behavior. A more sophisticated positivism would assert that we can rationally understand and predict even nonrational behavior. An example is the famous Asch experiment (Asch 1958). In this experiment, a group of subjects is presented with a set of lines on a screen and asked to identify the two lines that are equal in length. Imagine yourself a subject in such an experiment. You are sitting in the front row of a classroom in a group of six subjects. A set of lines is projected on the wall in front of you (see Figure 2-1). The experimenter asks each of you, one at a time, to identify the line to the right (A, B, or C) that matches the length of line X. The correct answer (B) is pretty obvious to you. To your surprise, however, you ﬁnd that all the other subjects agree on a different answer! The experimenter announces that all but one of the group has gotten the correct answer. Because

critical race theory A paradigm grounded in race awareness and an intention to achieve racial justice. interest convergence The thesis that majority group members will only support the interests of minorities when those actions also support the interests of the majority group.

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FIGURE 2-1 The Asch Experiment. Subjects in the Asch experiment have a seemingly easy task: to determine whether A, B, or C is the same length as .XBut there’s more here than meets the eye.

you are the only one who chose B, this amounts to saying that you’ve gotten it wrong. Then a new set of lines is presented, and you have the same experience. What seems to be the obviously correct answer is said by everyone else to be wrong. As it turns out, of course, you are the only real subject in this experiment—all the others are working with the experimenter. The purpose of the experiment is to see whether you will be swayed by public pressure to go along with the incorrect answer. In his initial experiments, all of which involved young men, Asch found that a little over one-third of his subjects did just that. Choosing an obviously wrong answer in a simple experiment is an example of nonrational behavior. But as Asch went on to show, experimenters can examine the circ*mstances that lead more or fewer subjects to go along with the incorrect answer. For example, in subsequent studies, Asch varied the size of one group and the number of “dissenters” who chose the “wrong” (that is, the correct) answer. Thus, it is possible to study nonrational behavior rationally and scientiﬁcally. More radically, we can question whether social life abides by rational principles at all. In the physical sciences, developments such as chaos theory, fuzzy logic, and complexity have suggested that we may need to rethink fundamentally the orderliness of events in the physical world. Certainly the social world might be no tidier than the world of physics.

The contemporary challenge to positivism, however, goes beyond the question of whether people behave rationally. In part, the criticism of positivism challenges the idea that scientists can be as objective as the positivistic ideal assumes. Most scientists would agree that personal feelings can and do inﬂuence the problems scientists choose to study, what they choose to observe, and the conclusions they draw from their observations. There is an even more radical critique of the ideal of objectivity. As we glimpsed in the discussions of feminism and ethnomethodology, some contemporary researchers suggest that subjectivity might actually be preferable in some situations. Let’s take a moment to return to the dialectic of subjectivity and objectivity. To begin, all our experiences are inescapably subjective. There is no way out. We can see only through our own eyes, and anything peculiar to our eyes will shape what we see. We can hear things only the way our particular ears and brain transmit and interpret sound waves. You and I, to some extent, hear and see different realities. And both of us experience quite different physical “realities” than, say, do bats. In what to us is total darkness, a bat “sees” things such as ﬂying insects by emitting a sound we humans can’t hear. The reﬂection of the bat’s sound creates a “sound picture” precise enough for the bat to home in on the moving insect and snatch it up in its teeth. In a similar vein, scientists on the planet Xandu might develop theories of the physical world based on a sensory apparatus that we humans can’t even imagine. Maybe they see X-rays or hear colors. Despite the inescapable subjectivity of our experience, we humans seem to be wired to seek an agreement on what is really real, what is objectively so. Objectivity is a conceptual attempt to get beyond our individual views. It is ultimately a matter of communication, as you and I attempt to ﬁnd a common ground in our subjective experiences. Whenever we succeed in our search, we say we are dealing with objective reality. This is the agreement reality discussed in Chapter 1. To this point, perhaps the most signiﬁcant studies in the history of social science were conducted in the 1930s by a Turkish American social

Some Social Science Paradigms psychologist, Muzafer Sherif (1935), who slyly said he wanted to study “auto-kinetic effects.” To do this, he put small groups in totally darkened rooms, save for a single point of light in the center of the wall in front of the participants. Sherif explained that the light would soon begin to move about, and the subjects were to determine how far it was moving—a difﬁcult task with nothing else visible as a gauge of length or distance. Amazingly, each of the groups agreed on the distance the point of light moved about. Oddly, however, the different groups of subjects arrived at quite different conclusions. Strangest of all—as you may have guessed—the point of light had remained stationary. If you stare at a ﬁxed point of light long enough it will seem to move about (Sherif’s “auto-kinetic effect”). Notice, however, that each of the groups agreed on a speciﬁc delusion. The movement of the light was real to them, but it was a reality created out of nothing: a socially constructed reality. Whereas our subjectivity is individual, then, our search for objectivity is social. This is true in all aspects of life, not just in science. While you and I prefer different foods, we must agree to some extent on what is ﬁt to eat and what is not, or else there could be no restaurants or grocery stores. The same argument could be made regarding every other form of consumption. Without agreement reality, there could be no movies or television, no sports. Social scientists as well have found beneﬁts in the concept of a socially agreed-on objective reality. As people seek to impose order on their experience of life, they ﬁnd it useful to pursue this goal as a collective venture. What are the causes and cures of prejudice? Working together, social researchers have uncovered some answers that hold up to intersubjective scrutiny. Whatever your subjective experience of things, for example, you can discover for yourself that as education increases, prejudice generally tends to decrease. Because each of us can discover this independently, we say that it is objectively true. From the seventeenth century through the middle of the twentieth, however, the belief in an objective reality that was independent of individual

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perceptions predominated in science. For the most part, it was not simply held as a useful paradigm but held as The Truth. The term positivism has generally represented the belief in a logically ordered, objective reality that we can come to know better and better through science. This is the view challenged today by postmodernists and others. Some say that the ideal of objectivity conceals as much as it reveals. As we saw earlier, in years past much of what was regarded as objectivity in Western social science was actually an agreement primarily among white, middle-class European men. Equally real experiences common to women, to ethnic minorities, to non-Western cultures, or to the poor were not necessarily represented in that reality. Thus, early anthropologists are now criticized for often making modern, Westernized “sense” out of the beliefs and practices of nonliterate tribes around the world, sometimes by portraying their subjects as superstitious savages. We often call orally transmitted beliefs about the distant past “creation myth,” whereas we speak of our own beliefs as “history.” Increasingly today, there is a demand to ﬁnd the native logic by which various peoples make sense out of life and to understand it on its own terms. Ultimately, we’ll never be able to distinguish completely between an objective reality and our subjective experience. We can’t know whether our concepts correspond to an objective reality or are simply useful in allowing us to predict and control our environment. So desperate is our need to know what is really real, however, that both positivists and postmodernists are sometimes drawn into the belief that their own view is real and true. There is a dual irony in this. On the one hand, the positivist’s belief that science precisely mirrors the objective world must ultimately be based on faith; it cannot be proved by “objective” science, because that’s precisely what’s at issue. And the postmodernists, who say nothing is objectively so and everything is ultimately subjective, do at least feel that that is really the way things are. Postmodernism is often portrayed as a denial of the possibility of social science. Because this book has already expressed sympathy for some

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postmodern views and concerns, a word of explanation may be in order. This textbook makes no assumption about the existence or absence of an objective reality. At the same time, human beings demonstrate an extensive and robust ability to establish agreements as to what’s “real.” This appears in regard to rocks and trees, as well as ghosts and gods, and even more elusive ideas such as loyalty and treason. Whether something like “prejudice” really exists, research into its nature can take place, because enough people agree that prejudice does exist, and researchers can use agreed-on techniques of inquiry to study it. Another social science paradigm, critical realism, suggests that we deﬁne “reality” as that which can be seen to have an effect. Since prejudice clearly has an observable effect in our lives, it must be judged “real” in terms of this point of view. This paradigm ﬁts interestingly with a statement attributed to an early U.S. sociologist, W. I. Thomas: ”If men deﬁne situations as real, they are real in their consequences.” This book will not require or even encourage you to choose among positivism, postmodernism, or any of the other paradigms discussed in this chapter. In fact, I invite you to look for value in any and all as you seek to understand the world that may or may not exist around you. Similarly, as social researchers, we are not forced to align ourselves entirely with either positivism or postmodernism. Instead, we can treat them as two distinct arrows in our quiver. Each approach compensates for the weaknesses of the other by suggesting complementary perspectives that can produce useful lines of inquiry. For example, the renowned British physicist Stephen Hawking has elegantly described the appealing simplicity of the positivistic model but tempers his remarks with a recognition of the way science is practiced.

postmodernism A paradigm that questions the assumptions of positivism and theories describing an “objective” reality. critical realism A paradigm that holds things are real insofar as they produce effects.

According to this way of thinking, a scientiﬁc theory is a mathematical model that describes and codiﬁes the observations we make. A good theory will describe a large range of phenomena on the basis of a few simple postulates and will make deﬁnite predictions that can be tested. If the predictions agree with the observations, the theory survives that test, though it can never be proved to be correct. On the other hand, if the observations disagree with the predictions, one has to discard or modify the theory. (At least, that is what is supposed to happen. In practice, people often question the accuracy of the observations and the reliability and moral character of those making the observations.) (2001: 31)

In summary, a rich variety of theoretical paradigms can be brought to bear on the study of social life. With each of these fundamental frames of reference, useful theories can be constructed. We turn now to some of the issues involved in theory construction, which are of interest and use to all social researchers, from positivists to postmodernists—and all those in between.

Elements of Social Theory As we have seen, paradigms are general frameworks or viewpoints: literally “points from which to view.” They provide ways of looking at life and are grounded in sets of assumptions about the nature of reality. Theories, by contrast, are systematic sets of interrelated statements intended to explain some aspect of social life. Thus, theories ﬂesh out and specify paradigms. Whereas a paradigm offers a way of looking, a theory aims at explaining what we see. Recall from Chapter 1 that social scientists engage in both idiographic and nomothetic explanations. Idiographic explanations seek to explain a limited phenomenon as completely as possible— explaining why a particular woman voted as she did, for example—while nomothetic explanations attempt to explain a broad range of phenomena

Elements of Social Theory at least partically: identifying a few factors that account for much voting behavior in general. Let’s look a little more deliberately now at some of the elements of a theory. As I mentioned in Chapter 1, science is based on observation. In social research, observation typically refers to seeing, hearing, and (less commonly) touching. A corresponding idea is fact. Although for philosophers “fact” is as complex a notion as “reality,” social scientists generally use it to refer to some phenomenon that has been observed. It is a fact, for example, that Barack Obama defeated John McCain in the 2008 presidential election. Scientists aspire to organize many facts under “rules” called laws. Abraham Kaplan (1964: 91) deﬁnes laws as universal generalizations about classes of facts. The law of gravity is a classic example: Bodies are attracted to each other in proportion to their masses and in inverse proportion to the distance separating them. Laws must be truly universal, however, not merely accidental patterns found among a speciﬁc set of facts. It is a fact, Kaplan points out (1964: 92), that in each of the U.S. presidential elections from 1920 to 1960, the major candidate with the longest name won. That is not a law, however, as shown by the next three elections. The earlier pattern was a coincidence. Sometimes called principles, laws are important statements about what is so. We speak of them as being “discovered,” granting, of course, that our paradigms affect what we choose to look for and what we see. Laws in and of themselves do not explain anything. They just summarize the way things are. Explanation is a function of theory, as we’ll see shortly. There are no social science laws that claim the universal certainty of those of the natural sciences. Social scientists debate among themselves whether such laws will ever be discovered. Perhaps social life essentially does not abide by invariant laws. This does not mean that social life is so chaotic as to defy prediction and explanation. As we saw in Chapter 1, social behavior falls into patterns, and those patterns quite often make perfect sense, although we may have to look below the surface to ﬁnd the logic.

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As I just indicated, laws should not be confused with theories. Whereas a law is an observed regularity, a theory is a systematic explanation for observations that relate to a particular aspect of life. For example, someone might offer a theory of juvenile delinquency, prejudice, or political revolution. Theories explain observations by means of concepts. Jonathan Turner (1989: 5) calls concepts the “basic building blocks of theory.” Concepts are abstract elements representing classes of phenomena within the ﬁeld of study. The concepts relevant to a theory of juvenile delinquency, for example, include “juvenile” and “delinquency,” for starters. A “peer group”—the people you hang around with and identify with—is another relevant concept. “Social class” and “ethnicity” are undoubtedly relevant concepts in a theory of juvenile delinquency. “School performance” might also be relevant. A variable is a special kind of concept. Some of the concepts just mentioned refer to things, and others refer to sets of things. As we saw in Chapter 1, each variable comprises a set of attributes; thus, delinquency, in the simplest case, is made up of delinquent and not delinquent. A theory of delinquency would aim at explaining why some juveniles are delinquent and others are not. Axioms or postulates are fundamental assertions, taken to be true, on which a theory is grounded. In a theory of juvenile delinquency, we might begin with axioms such as “Everyone desires material comforts” and “The ability to obtain material comforts legally is greater for the wealthy than for the poor.” From these we might proceed to propositions: speciﬁc conclusions, derived from the axiomatic groundwork, about the relationships among concepts. From our beginning axioms about juvenile delinquency, for example, we might reasonably formulate the proposition that poor youths are more likely to break the law to gain material comforts than are rich youths. This proposition, incidentally, accords with Robert Merton’s classic attempt to account for deviance in society. Merton (1957: 139–57) spoke of the agreed-on means and ends of a society. In Merton’s model, nondeviants are those who share the societal agreement as to desired ends (such as a new car) and the means prescribed for achieving

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them (such as to buy it). One type of deviant— Merton called this type the “innovator”—agrees on the desired end but does not have access to the prescribed means for achieving it. Innovators ﬁnd another method, such as crime, of getting the desired end. From propositions, in turn, we can derive hypotheses. A hypothesis is a speciﬁed testable expectation about empirical reality that follows from a more general proposition. Thus, a researcher might formulate the hypothesis, “Poor youths have higher delinquency rates than do rich youths.” Research is designed to test hypotheses. In other words, research will support (or fail to support) a theory only indirectly—by testing speciﬁc hypotheses that are derived from theories and propositions. Let’s look more clearly at how theory and research come together.

Two Logical Systems Revisited In Chapter 1, I introduced deductive and inductive reasoning, with a promise that we would return to them later. It’s later.

The Traditional Model of Science Most of us have a somewhat idealized picture of “the scientiﬁc method,” a view gained from science instruction ever since elementary school, especially in the physical sciences. Although this traditional model of science tells only a part of the story, it’s helpful to understand its logic.

hypothesis A speciﬁed testable expectation about empirical reality that follows from a more general proposition; more generally, an expectation about the nature of things derived from a theory. It is a statement of something that ought to be observed in the real world if the theory is correct. operationalization One step beyond conceptualization. Operationalization is the process of developing operational deﬁnitions, or specifying the exact operations involved in measuring a variable.

There are three main elements in the traditional model of science: theory, operationalization, and observation. At this point we’re already well acquainted with the idea of theory.

Theory According to the traditional model of science, scientists begin with a thing, from which they derive testable hypotheses. So, for example, as social scientists we might have a theory about the causes of juvenile delinquency. Let’s assume that we have arrived at the hypothesis that delinquency is inversely related to social class. That is, as social class goes up, delinquency goes down.

Operationalization To test any hypothesis, we must specify the meanings of all the variables involved in it, in observational terms. In the present case, the variables are social class and delinquency. To give these terms speciﬁc meaning, we might deﬁne delinquency as “being arrested for a crime,” “being convicted of a crime,” or some other plausible phrase, whereas social class might be speciﬁed in terms of family income, for the purposes of this particular study. Once we have deﬁned our variables, we need to specify how we’ll measure them. (Recall from Chapter 1 that science, in the classical ideal, depends on measurable observations.) Operationalization literally means specifying the exact operations involved in measuring a variable. There are many ways we can attempt to test our hypothesis, each of which allows for different ways of measuring our variables. For simplicity, let’s assume we’re planning to conduct a survey of high school students. We might operationalize delinquency in the form of the question “Have you ever stolen anything?” Those who answer “yes” will be classiﬁed as delinquents in our study; those who say “no” will be classiﬁed as nondelinquents. Similarly, we might operationalize social class by asking respondents, “What was your family’s income last year?” and providing them with a set of family income categories: under $10,000; $10,000–$24,999; $25,000–$49,999; and $50,000 and above.

Two Logical Systems Revisited At this point someone might object that delinquency can mean something more than or different from having stolen something at one time or another, or that social class isn’t necessarily the same as family income. Some parents might think body piercing is a sign of delinquency even if their children don’t steal, and to some social class might include an element of prestige or community standing as well as how much money a family has. For the researcher testing a hypothesis, however, the meaning of variables is exactly and only what the operational deﬁnition speciﬁes. In this respect, scientists are very much like Humpty Dumpty in Lewis Carroll’s Through the Looking Glass. “When I use a word,” Humpty Dumpty tells Alice, “it means just what I choose it to mean—neither more nor less.” “The question is,” Alice replies, “whether you can make words mean so many different things.” To which Humpty Dumpty responds, “The question is, which is to be master—that’s all.” Scientists have to be “masters” of their operational deﬁnitions for the sake of precision in observation, measurement, and communication. Otherwise, we would never know whether a study that contradicted ours did so only because it used a different set of procedures to measure one of the variables and thus changed the meaning of the hypothesis being tested. Of course, this also means that to evaluate a study’s conclusions about juvenile delinquency and social class, or any other variables, we need to know how those variables were operationalized. The way we have operationalized the variables in our imaginary study could be open to other problems, however. Perhaps some respondents will lie about having stolen anything, in which cases we’ll misclassify them as nondelinquent. Some respondents will not know their family incomes and will give mistaken answers; others may be embarrassed and lie. We’ll consider issues like these in detail in Part 2. Our operationalized hypothesis now is that the highest incidence of delinquents will be found among respondents who select the lowest family income category (under $10,000); a lower percentage of delinquents will be found in the $10,000–

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$24,999 category; still fewer delinquents will be found in the $25,000–$49,999 category; and the lowest percentage of delinquents will be found in the $50,000-and-above category. Now we’re ready for the ﬁnal step in the traditional model of science— observation. Having developed theoretical clarity and speciﬁc expectations, and having created a strategy for looking, all that remains is to look at the way things actually are.

Observation The ﬁnal step in the traditional model of science involves actual observation, looking at the world and making measurements of what is seen. Let’s suppose our survey produced the following data: Percent delinquent

Under $10,000 $10,000–$24,999 $25,000–$49,999 $50,000 and above

20 15 10 5

Observations producing such data would conﬁrm our hypothesis. But suppose our ﬁndings were as follows: Percent delinquent

Under $10,000 $10,000–$24,999 $25,000–$49,999 $50,000 and above

15 15 15 15

These ﬁndings would disconﬁrm our hypothesis regarding family income and delinquency. Disconﬁrmability—the possibility that observations may not support our expectations—is an essential quality of any hypothesis. In other words, if

operational deﬁnition The concrete and speciﬁc deﬁnition of something in terms of the operations by which observations are to be categorized. The operational deﬁnition of “earning an A in this course” might be “correctly answering at least 90 percent of the ﬁnal exam questions.”

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there is no chance that our hypothesis will be disconﬁrmed, it hasn’t said anything meaningful. For example, the hypothesis that juvenile delinquents commit more crimes than do nondelinquents cannot possibly be disconﬁrmed, because criminal behavior is intrinsic to the idea of delinquency. Even if we recognize that some young people commit crimes without being caught and labeled as delinquents, they couldn’t threaten our hypothesis, because our actual observations would lead us to conclude they were law-abiding nondelinquents. Figure 2-2 provides a schematic diagram of the traditional model of scientiﬁc inquiry. In it we see the researcher beginning with an interest in a phenomenon (such as juvenile delinquency). Next comes the development of a theoretical understanding, in this case that a single concept (such as social class) might explain others. The theoretical considerations result in an expectation about what should be observed if the theory is correct. The notation X f(Y) is a conventional way of saying that X (for example, delinquency) is a function of (depends on) Y (for example, social class). At that level, however, X and Y still have rather general meanings that could give rise to quite different observations and measurements. Operationalization speciﬁes the procedures that will be used to measure the variables. The lowercase x in Figure 2-2, for example, is a precisely measurable indicator of capital X. This operationalization process results in the formation of a testable hypothesis: for example, self-reported theft is a function of family income. Observations aimed at ﬁnding out whether this statement accurately describes reality are part of what is typically called hypothesis testing. (See “Hints for Stating Hypotheses” for more on the process of formulating hypotheses.)

Deductive and Inductive Reasoning: A Case Illustration As you probably recognized, the traditional model of science just described is a nice example of deductive reasoning: From a general theoretical understanding, the researcher derives (deduces) an expectation and ﬁnally a testable hypothesis. This

FIGURE 2-2 The Traditional Image of Science. The deductive model of scientiﬁc inquiry begins with a sometimes vague or general question, which is subjected to a process of speciﬁcation, resulting in hypotheses that can be tested through empirical observations.

picture is tidy, but in reality science uses inductive reasoning as well. Let’s consider a real research example as a vehicle for comparing the deductive and inductive linkages between theory and research. Years ago, Charles Glock, Benjamin Ringer, and I (1967) set out to discover what caused differing levels of church involvement among U.S. Episcopalians. Several theoretical or quasi-theoretical positions suggested possible answers. I’ll focus on only one here: what we came to call the “Comfort Hypothesis.” In part, we took our lead from the Christian injunction to care for “the halt, the lame, and the blind” and those who are “weary and heavy laden.” At the same time, ironically, we noted the Marxist assertion that religion is an “opiate for the masses.” Given both, it made sense to expect the following, which was our hypothesis: “Parishioners whose life situations most deprive them of satisfaction and fulﬁllment in the secular society turn to

Two Logical Systems Revisited

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Hints for Stating Hypotheses

Riley E. Dunlap Department of Sociology, Oklahoma State University

hypothesis is the basic statement that is tested in research. Typically a hypothesis states a relationship between two variables. (Although it is possible to use more than two variables, you should stick to two for now.) Because a hypothesis makes a prediction about the relationship between the two variables, it must be testable so you can determine if the prediction is right or wrong when you examine the results obtained in your study. A hypothesis must be stated in an unambiguous manner to be clearly testable. What follows are suggestions for developing testable hypotheses. Assume you have an interest in trying to predict some phenomenon such as “attitudes toward women’s liberation,” and that you can measure such attitudes on a continuum ranging from “opposed to women’s liberation” to “neutral” to “supportive of women’s liberation.” Also assume that, lacking a theory, you’ll rely on “hunches” to come up with variables that might be related to attitudes toward women’s liberation. In a sense, you can think of hypothesis construction as a case of ﬁlling in the blank:“_____ is related to attitudes toward women’s liberation.“ Your job is to think of a variable that might plausibly be related to such attitudes, and then to word a hypothesis that states a relationship between the two variables (the one that ﬁlls in the “blank” and “attitudes toward women’s liberation”). You need to do so in a precise manner so that you can determine clearly whether the hypothesis is supported or not when you examine the results (in this case, most likely the results of a survey). The key is to word the hypothesis carefully so that the prediction it makes is quite clear to you as well as others. If you use age, note that saying “Age is related to attitudes toward women’s liberation” does not say precisely how you think the two are related (in fact, the only way this hypothesis could be falsiﬁed is if you fail to ﬁnd a statistically signiﬁcant relationship of any type between age and attitudes toward women’s liberation). In this case a couple of steps are necessary. You have two options: 1.

“Age is related to attitudes toward women’s liberation, with younger adults being more supportive than older adults.” (Or, you could state the opposite, if you believed older people are likely to be more supportive.) “Age is negatively related to support for women’s liberation.” Note here that I specify “support” for women’s liberation (SWL) and then predict a negative relationship—that is, as age goes up, I predict that SWL will go down.

In this hypothesis, note that both of the variables (age, the independent variable or likely “cause,” and SWL, the dependent variable or likely “effect”) range from low to high. This feature of the two variables is what allows you to use “negatively” (or “positively”) to describe the relationship. Notice what happens if you hypothesize a relationship between gender and SWL. Because gender is a nominal variable (as you’ll learn in Chapter 5) it does not range from low to high—people are either male or female (the two attributes of the variable gender). Consequently, you must be careful in stating the hypothesis unambiguously: 1.

“Gender is positively (or negatively) related to SWL” is not an adequate hypothesis, because it doesn’t specify how you expect gender to be related to SWL—that is, whether you think men or women will be more supportive of women’s liberation. It’s tempting to say something like “Women are positively related to SWL,” but this really doesn’t work, because female is only an attribute, not a full variable (gender is the variable). “Gender is related to SWL, with women being more supportive than men” would be my recommendation. Or, you could say, “with men being less supportive than women,” which makes the identical prediction. (Of course, you could also make the opposite prediction, that men are more supportive than women are, if you wished.) Equally legitimate would be “Women are more likely to support women’s liberation than are men.” (Note the need for the second “are,” or you could be construed as hypothesizing that women support women’s liberation more than they support men—not quite the same idea.)

The above examples hypothesized relationships between a “characteristic” (age or gender) and an “orientation” (attitudes toward women’s liberation). Because the causal order is pretty clear (obviously age and gender come before attitudes, and are less alterable), we could state the hypotheses as I’ve done, and everyone would assume that we were stating causal hypotheses. Finally, you may run across references to the null hypothesis, especially in statistics. Such a hypothesis predicts no relationship (technically, no statistically signiﬁcant relationship) between the two variables, and it is always implicit in testing hypotheses. Basically, if you have hypothesized a positive (or negative) relationship, you are hoping that the results will allow you to reject the null hypothesis and verify your hypothesized relationship.

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the church for comfort and substitute rewards” (Glock, Ringer, and Babbie 1967: 107–8). Having framed this general hypothesis, we set about testing it. Were those deprived of satisfaction in the secular society in fact more religious than those who received more satisfaction from the secular society? To answer this, we needed to distinguish who was deprived. The questionnaire, which was constructed for the purpose of testing the Comfort Hypothesis, included items that seemed to offer indicators of whether parishioners were relatively deprived or gratiﬁed in secular society. To start, we reasoned that men enjoy more status than women do in our generally male-dominated society. Though hardly novel, this conclusion laid the groundwork for testing the Comfort Hypothesis. If we were correct in our hypothesis, women should appear more religious than men. Once the survey data had been collected and analyzed, our expectation about gender and religion was clearly conﬁrmed. On three separate measures of religious involvement—ritual (such as church attendance), organizational (such as belonging to church organizations), and intellectual (such as reading church publications)—women were more religious than men. On our overall measure, women scored 50 percent higher than men. In another test of the Comfort Hypothesis, we reasoned that in a youth-oriented society, old people would be more deprived of secular gratiﬁcation than the young would. Once again, the data conﬁrmed our expectation. The oldest parishioners were more religious than the middle-aged, who were more religious than young adults. Social class—measured by education and income—afforded another test of the Comfort Hypothesis. Once again, the test succeeded. Those with low social status were more involved in the church than those with high social status were.

null hypothesis In connection with hypothesis testing and tests of statistical signiﬁcance, that hypothesis that suggests there is no relationship among the variables under study. You may conclude that the variables are related after having statistically rejected the null hypothesis.

The hypothesis was even conﬁrmed in a test that went against everyone’s commonsense expectations. Despite church posters showing worshipful young families and bearing the slogan “The Family That Prays Together Stays Together,” the Comfort Hypothesis suggested that parishioners who were married and had children—the clear American ideal at that time—would enjoy secular gratiﬁcation in that regard. As a consequence, they should be less religious than those who lacked one or both family components. Thus, we hypothesized that parishioners who were both single and childless should be the most religious; those with either spouse or child should be somewhat less religious; and those married with children—representing the ideal pictured on all those posters—should be the least religious of all. That’s exactly what we found. Finally, the Comfort Hypothesis suggested that the various kinds of secular deprivation should be cumulative: Those with all the characteristics associated with deprivation should be the most religious; those with none should be the least. When we combined the four individual measures of deprivation into a composite measure, the theoretical expectation was exactly conﬁrmed. Comparing the two extremes, we found that single, childless, elderly, lower-class female parishioners scored more than three times as high on the measure of church involvement than did young, married, upper-class fathers. Thus was the Comfort Hypothesis conﬁrmed. I like this research example because it so clearly illustrates the logic of the deductive model. Beginning with general, theoretical expectations about the impact of social deprivation on church involvement, one could derive concrete hypotheses linking speciﬁc measurable variables, such as age and church attendance. The actual empirical data could then be analyzed to determine whether empirical reality supported the deductive expectations. I say this example shows how it was possible to do it that way, but, alas, I’ve been ﬁbbing. To tell the truth, although we began with an interest in discovering what caused variations in church involvement among Episcopalians, we didn’t actually begin with a Comfort Hypothesis, or any

Two Logical Systems Revisited other hypothesis for that matter. (In the interest of further honesty, Glock and Ringer initiated the study, and I joined it years after the data had been collected.) A questionnaire was designed to collect information that might shed some light on why some parishioners participated in the church more than others, but the construction of the questionnaire was not guided by any precise, deductive theory. Once the data were collected, the task of explaining differences in religiosity began with an analysis of variables that have a wide impact on people’s lives, including gender, age, social class, and family status. Each of these four variables was found to relate strongly to church involvement, in the ways already described. Indeed, they had a cumulative effect, also already described. Rather than being good news, however, this presented a dilemma. Glock recalls discussing his ﬁndings with colleagues over lunch at the Columbia faculty club. Once he had displayed the tables illustrating the impact of each individual variable as well as their powerful composite effect, a colleague asked, “What does it all mean, Charlie?” Glock was at a loss. Why were those variables so strongly related to church involvement? That question launched a process of reasoning about what the several variables had in common, aside from their impact on religiosity. Eventually he saw that each of the four variables also reﬂected differential status in the secular society. He then had the thought that perhaps the issue of comfort was involved. Thus, the inductive process had moved from concrete observations to a general theoretical explanation. It seems easier to lay out the steps involved in deductive than inductive research. Deductive research begins with a theory, from which we may derive hypotheses—which are then tested through observations. Inductive research begins with observations and proceeds with a search for patterns in what we have observed. In a quantitative study, we can search for correlations or relationships between variables (discussed further in Chapter 16). Thus, once a relationship has been discovered between gender and religiosity, our attention turns to ﬁguring out logical reasons why that is so.

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Most qualitative research is oriented toward the inductive rather than the deductive approach. However, qualitative research does not, by deﬁnition, allow us to use statistical tools to ﬁnd correlations that point toward patterns in need of explanation (see Chapter 14). Although there are computer programs designed for recording and analyzing qualitative data, the qualitative inductive analyst needs a strong reserve of insight and reﬂection to tease important patterns out of a body of observations.

A Graphic Contrast As the preceding case illustration shows, theory and research can usefully be done both inductively and deductively. Figure 2-3 shows a graphic comparison of the two approaches as applied to an inquiry into study habits and performance on exams. In both cases, we are interested in the relationship between the number of hours spent studying for an exam and the grade earned on that exam. Using the deductive method, we would begin by examining the matter logically. Doing well on an exam reﬂects a student’s ability to recall and manipulate information. Both of these abilities should be increased by exposure to the information before the exam. In this fashion, we would arrive at a hypothesis suggesting a positive relationship between the number of hours spent studying and the grade earned on the exam. We say “positive” because we expect grades to increase as the hours of studying increase. If increased hours produced decreased grades, that would be called a negative, or inverse, relationship. The hypothesis is represented by the line in part 1(a) of Figure 2-3. Our next step would be to make observations relevant to testing our hypothesis. The shaded area in part 1(b) of the ﬁgure represents perhaps hundreds of observations of different students, speciﬁcally, how many hours they studied and what grades they received. Finally, in part 1(c), we compare the hypothesis and the observations. Because observations in the real world seldom if ever match our expectations perfectly, we must decide whether the match is close enough to consider

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FIGURE 2-3 Deductive and Inductive eMthods. Both deduction and induction are legitimate and valuable approaches to understanding. Deduction begins with an expected pattern that is tested against observations, whereas induction begins with observations and seeks to ﬁnd a pattern within them. the hypothesis conﬁrmed. Put differently, can we conclude that the hypothesis describes the general pattern that exists, granting some variations in real life? Sometimes, answering this question necessitates methods of statistical analysis, which will be discussed in Part 4. Now suppose we used the inductive method to address the same research question. In this case, we

would begin with a set of observations, as in part 2(a) of Figure 2-3. Curious about the relationship between hours spent studying and grades earned, we might simply arrange to collect relevant data. Then we’d look for a pattern that best represented or summarized our observations. In part 2(b) of the ﬁgure, the pattern is shown as a curved line running through the center of our observations.

Deductive Theory Construction The pattern found among the points in this case suggests that with 1 to 15 hours of studying, each additional hour generally produces a higher grade on the exam. With 15 to about 25 hours, however, more study seems to lower the grade slightly. Studying more than 25 hours, on the other hand, results in a return to the initial pattern: More hours produce higher grades. Using the inductive method, then, we end up with a tentative conclusion about the pattern of the relationship between the two variables. The conclusion is tentative because the observations we have made cannot be taken as a test of the pattern—those observations are the source of the pattern we’ve created. As I discussed in Chapter 1, in actual practice, theory and research interact through a never-ending alternation of deduction and induction. A good example is the classic work of Emile Durkheim on suicide ([1897] 1951). When Durkheim pored over table after table of ofﬁcial statistics on suicide rates in different areas, he was struck by the fact that Protestant countries consistently had higher suicide rates than Catholic ones did. Why should that be the case? His initial observations led him to create inductively a theory of religion, social integration, anomie, and suicide. His theoretical explanations in turn led deductively to further hypotheses and further observations. In summary, the scientiﬁc norm of logical reasoning provides a two-way bridge between theory and research. Scientiﬁc inquiry in practice typically involves alternating between deduction and induction. Both methods involve an interplay of logic and observation. And both are routes to the construction of social theories. Although both inductive and deductive methods are valid in scientiﬁc inquiry, individuals may feel more comfortable with one approach than the other. Consider this exchange in Sir Arthur Conan Doyle’s story “A Scandal in Bohemia,” as Sherlock Holmes answers Dr. Watson’s inquiry (Doyle [1891] 1892: 13): “What do you imagine that it means?” “I have no data yet. It is a capital mistake to theorise before one has data. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts.”

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Some social scientists would more or less agree with this inductive position (see especially the dis-cussion of grounded theory in Chapter 10), whereas others would take a more deductive stance. Most, however, concede the legitimacy of both approaches. With this understanding of the deductive and inductive links between theory and research in hand, let’s now delve a little more deeply into how theories are constructed using either of these two different approaches.

Deductive Theory Construction To see what’s involved in deductive theory construction and hypothesis testing, imagine that you’re going to construct a deductive theory. How would you go about it?

Getting Started The ﬁrst step in deductive theory construction is to pick a topic that interests you. The topic can be very broad, such as “What is the structure of society?” or it can be narrower, as in “Why do people support or oppose the idea of a woman’s right to an abortion?” Whatever the topic, it should be something you’re interested in understanding and explaining. Once you’ve picked your topic, the next step is to undertake an inventory of what’s already known or thought about it. In part, this means writing down your own observations and ideas. Beyond that, it means learning what other scholars have said about it. You can talk to other people, and you’ll want to read the scholarly literature on the topic. Appendix A provides guidelines for using the library—you’ll likely spend a lot of time there. Your preliminary research will probably uncover consistent patterns discovered by prior scholars. For example, religious and political variables will stand out as important determinants of attitudes about abortion. Findings such as these will be very useful to you in creating your own theory. In this process, don’t overlook the value of introspection. Whenever we can look at our own personal processes—including reactions, fears, and prejudices—we may gain important insights into

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human behavior in general. I don’t mean to say that everyone thinks like you or me, but introspection can provide a useful source of insights that can inform our inquiries.

Constructing Your Theory Now that you’ve reviewed previous work on the topic, you’re ready to begin constructing your theory. Although theory construction is not a lockstep affair, the process generally involves something like the following steps. 1. Specify the topic. 2. Specify the range of phenomena your theory addresses. Will your theory apply to all of human social life, will it apply only to U.S. citizens, only to young people, or what? 3. Identify and specify your major concepts and variables. 4. Find out what is known (propositions) about the relationships among those variables. 5. Reason logically from those propositions to the speciﬁc topic you’re examining. We’ve already discussed items (1) through (3), so let’s focus now on (4) and (5). As you identify the relevant concepts and discover what’s already been learned about them, you can begin to create a propositional structure that explains the topic under study. Let’s look now at an example of how these building blocks ﬁt together in deductive theory construction and empirical research.

An Example of Deductive Theory: Distributive Justice A topic of interest to scholars is the concept of distributive justice, people’s perceptions of whether they are being treated fairly by life, whether they are getting “their share.” Guillermina Jasso describes the theory of distributive justice more formally, as follows: The theory provides a mathematical description of the process whereby individuals, reﬂecting on their holdings of the goods they value (such

as beauty, intelligence, or wealth), compare themselves to others, experiencing a fundamental instantaneous magnitude of the justice evaluation (J), which captures their sense of being fairly or unfairly treated in the distributions of natural and social goods. (Jasso 1988: 11)

Notice that Jasso has assigned a symbolic representation for her key variable: J will stand for distributive justice. She does this to support her intention of stating her theory in mathematical formulas. Though theories are often expressed mathematically, we’ll not delve too deeply into that practice here. Jasso indicates that there are three kinds of postulates in her theory. “The ﬁrst makes explicit the fundamental axiom which represents the substantive point of departure for the theory.” She elaborates as follows: “The theory begins with the received Axiom of Comparison, which formalizes the long-held view that a wide class of phenomena, including happiness, self-esteem, and the sense of distributive justice, may be understood as the product of a comparison process” (Jasso 1988: 11). Thus, your sense of whether you’re receiving a “fair” share of the good things of life comes from comparing yourself with others. If this seems obvious to you, that’s not a shortcoming of the axiom. Remember, axioms are the taken-for-granted beginnings of theory. Jasso continues to do the groundwork for her theory. First, she indicates that our sense of distributive justice is a function of “Actual Holdings (A)” and “Comparison Holdings (C)” of some good. Let’s consider money, for example. My sense of justice in this regard is a function of how much I actually have, compared with how much others have. By specifying the two components of the comparison, Jasso can use them as variables in her theory. Next, Jasso offers a “measurement rule” that further speciﬁes how the two variables, A and C, will be conceptualized. This step is needed because some of the goods to be examined are concrete and commonly measured (such as money), whereas others are less tangible (such as respect). The former kind, she says, will be measured conventionally, whereas the latter will be measured “by

Deductive Theory Construction the individual’s relative rank . . . within a specially selected comparison group.” The theory will provide a formula for making that measurement (Jasso 1988: 13). Jasso continues in this fashion to introduce additional elements, weaving them into mathematical formulas to be used in deriving predictions about the workings of distributive justice in a variety of social settings. Here is just a sampling of where her theorizing takes her (1988: 14–15).

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Other things [being] the same, a person will prefer to steal from a fellow group member rather than from an outsider.

•

The preference to steal from a fellow group member is more pronounced in poor groups than in rich groups.

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In the case of theft, informants arise only in cross-group theft, in which case they are members of the thief’s group.

•

Persons who arrive a week late at summer camp or for freshman year of college are more likely to become friends of persons who play games of chance than of persons who play games of skill.

•

A society becomes more vulnerable to deﬁcit spending as its wealth increases.

•

Societies in which population growth is welcomed must be societies in which the set of valued goods includes at least one quantitygood, such as wealth.

Jasso’s theory leads to many other propositions, but this sampling should provide a good sense of where deductive theorizing can take you. To get a feeling for how she reasons her way to these propositions, let’s look brieﬂy at the logic involved in two of the propositions that relate to theft within and outside one’s group.

•

Other things [being] the same, a person will prefer to steal from a fellow group member rather than from an outsider.

Beginning with the assumption that thieves want to maximize their relative wealth, ask yourself whether that goal would be best served by stealing from those you compare yourself with or from outsiders. In each case, stealing will increase your

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Actual Holdings, but what about your Comparison Holdings? A moment’s thought should suggest that stealing from people in your comparison group will lower their holdings, further increasing your relative wealth. To simplify, imagine there are only two people in your comparison group: you and I. Suppose we each have $100. If you steal $50 from someone outside our group, you will have increased your relative wealth by 50 percent compared with me: $150 versus $100. But if you steal $50 from me, you will have increased your relative wealth 200 percent: $150 to my $50. Your goal is best served by stealing from within the comparison group.

•

In the case of theft, informants arise only in cross-group theft, in which case they are members of the thief’s group.

Can you see why it would make sense for informants (1) to arise only in the case of cross-group theft and (2) to come from the thief’s comparison group? This proposition again depends on the fundamental assumption that everyone wants to increase his or her relative standing. Suppose you and I are in the same comparison group, but this time the group contains additional people. If you steal from someone else within our comparison group, my relative standing in the group does not change. Although your wealth has increased, the average wealth in the group remains the same (because someone else’s wealth has decreased by the same amount). So my relative standing remains the same. I have no incentive to inform on you. If you steal from someone outside our comparison group, however, your nefarious income increases the total wealth in our group. Now my own wealth relative to that total is diminished. Because my relative wealth has suffered, I’m more likely to inform on you in order to bring an end to your stealing. Hence, informants arise only in cross-group theft. This last deduction also begins to explain why these informants come from the thief’s own comparison group. We’ve just seen how your theft decreased my relative standing. How about members of the other group (other than the individual you stole from)? Each of them actually proﬁts from

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How to Do It: Framing a Hypothesis

s we have seen, the deductive method of research typically focuses on the testing of a hypothesis. Let’s take a minute to look at how to create a hypothesis for testing. Hypotheses state an expected causal relationship between two (or more) variables. Let’s suppose you’re interested in student political orientations, and your review of the literature and your own reasoning suggest to you that college major will play some part in determining students’ political views. Already, we have two variables: college major and political orientation. Moreover, political orientation is the dependent variable—you believe it depends on something else, on the independent variable, which in this case is college major. Now we need to specify the attributes comprising each of these variables. For simplicity’s sake, let’s assume political orientation includes only liberal or conservative. And to simplify the matter of major, let’s suppose your research interests focus on the presumed differences between business students and those in the social sciences. Even with these simpliﬁcations, you would need to specify more concretely how you would recognize a liberal or a conservative when

the theft, because you have reduced the total with which they compare themselves. Hence, they have no reason to inform on you. Thus, the theory of distributive justice predicts that informants arise from the thief’s own comparison group. This brief peek into Jasso’s derivations should give you some sense of the enterprise of deductive theory. Of course, the theory guarantees none of the given predictions. The role of research is to test each of them to determine whether what makes sense (logic) actually occurs in practice (observation). See “How to Do It: Framing a Hypothesis” for a look at creating hypotheses for deductive purposes.

Inductive Theory Construction As we have seen, quite often social scientists begin constructing a theory through the inductive method by ﬁrst observing aspects of social life and

you came across them in your study. This process of speciﬁcation will be discussed at length in Chapter 5. For now, let’s assume you will ask student-subjects whether they consider themselves liberals or conservatives, letting each student report on what the terms mean to them. (As we’ll see later, this simple dichotomy is unlikely to work in practice, as some students would want to identify themselves as independents or something else.) Identifying students’ majors isn’t as straightforward as you might think. For example, what disciplines compose the social sciences in your study? Also, must students be declared majors or simply be planning to major in one of the relevant ﬁelds? Once these issues have been settled, you are ready to state your hypothesis. For example, it might be the following: “Students majoring in the social sciences will be more likely to identify themselves as liberals than are those majoring in business.” In addition to this basic expectation, you may wish to specify “more likely” in terms of how much more likely. Chapter 16 will provide some options in this regard.

then seeking to discover patterns that may point to relatively universal principles. Barney Glaser and Anselm Strauss (1967) coined the term grounded theory in reference to this method. Field research—the direct observation of events in progress—is frequently used to develop theories through observation. In a long and rich tradition, anthropologists have used this method to good advantage. Among modern social scientists, no one has been more adept at seeing the patterns of human behavior through observation than Erving Goffman: A game such as chess generates a habitable universe for those who can follow it, a plane of being, a cast of characters with a seemingly unlimited number of different situations and acts through which to realize their natures and destinies. Yet much of this is reducible to a small set of interdependent rules and practices. If the meaningfulness of everyday activity is similarly dependent on a closed, ﬁnite set of rules, then

Inductive Theory Construction explication of them would give one a powerful means of analyzing social life. (1974: 5)

In a variety of research efforts, Goffman uncovered the rules of such diverse behaviors as living in a mental institution (1961) and managing the “spoiled identity” of being disﬁgured (1963). In each case, Goffman observed the phenomenon in depth and teased out the rules governing behavior. Goffman’s research provides an excellent example of qualitative ﬁeld research as a source of grounded theory. Our earlier discussion of the Comfort Hypothesis and church involvement shows that qualitative ﬁeld research is not the only method of observation appropriate to the development of inductive theory. Here’s another detailed example to illustrate further the construction of inductive theory using quantitative methods.

An Example of Inductive Theory: Why Do People Smoke Marijuana? During the 1960s and 1970

The Practice of Social Research (12th Edition) - PDF Free Download (2024)

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