Cloth: 978-0-226-70273-5 | Paper: 978-0-226-70275-9 | Electronic: 978-0-226-70279-7
DOI: 10.7208/chicago/9780226702797.001.0001
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ABOUT THIS BOOK
Redesigning Social Inquiry provides a substantive critique of the standard approach to social research—namely, assessing the relative importance of causal variables drawn from competing theories. Instead, Ragin proposes the use of set-theoretic methods to find a middle path between quantitative and qualitative research. Through a series of contrasts between fuzzy-set analysis and conventional quantitative research, Ragin demonstrates the capacity for set-theoretic methods to strengthen connections between qualitative researchers’ deep knowledge of their cases and quantitative researchers’ elaboration of cross-case patterns. Packed with useful examples, Redesigning Social Inquiry will be indispensable to experienced professionals and to budding scholars about to embark on their first project.
AUTHOR BIOGRAPHY
REVIEWS
“Charles Ragin’s Redesigning Social Inquiry offers social scientists, both qualitative and quantitative, and their readers new ways to analyze social phenomena clearly, honestly, and effectively. Readers prepared to invest a few hours will find a new world of analytic possibilities and understanding open to them. Imagine having techniques, easy to understand and implement, whose results really speak to questions we all care about!”
“Redesigning Social Inquiry is aimed at social scientists looking to escape the banality of everyday quantitative research, and here they’ll find a sophisticated way out of all the by-the-numbers work. But this book also speaks to those of us who have a profound knowledge of cases and want to explore the implications of this understanding. With this rigorous yet accessible book, Charles Ragin has completed his mission to reorient social science.”
TABLE OF CONTENTS
Acknowledgments
Introduction
PART I: Set-Theoretic versus Correlational Connections
1: Set Relations in Social Research: Basic Concepts
2: Fuzzy Sets and Fuzzy-Set Relations
3: Evaluating Set Relations: Consistency and Coverage
PART II: Calibration versus Measurement
4: Why Calibrate?
5: Calibrating Fuzzy Sets
PART III: Configurations of Conditions versus “Independent” Variables
6: Configurational Thinking
7: Configurational Analysis Using Fuzzy Sets and Truth Tables
PART IV: Analysis of Causal Complexity versus Analysis of Net Effects
8: Limited Diversity and Counterfactual Cases
9: Easy versus Difficult Counterfactuals
10: The Limitations of Net Effects Thinking
11: Net Effects versus Configurations: An Empirical Demonstration
References
Index