In this innovative approach to the practice of social scienceÇharles Ragin explores the use of fuzzy sets to bridge the divide between quantitive and qualitative methods. He argues that fuzzy sets allow a far richer dialogue between ideas and evidence in social research than previously possible.
For over twenty years Charles C. Ragin has been at the forefront of the development of innovative methods for social scientists. In Redesigning Social Inquiry, he continues his campaign to revitalize the field, challenging major aspects of the conventional template for social science research while offering a clear alternative. 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.
This book introduces fuzzy set theory to social science researchers. Fuzzy sets are categories with blurred boundaries. With classical sets, objects are either in the set or not, but objects can belong partially to more than one fuzzy set at a time. Many concepts in the social sciences have this characteristic, and fuzzy set theory provides methods for systematically dealing with them. A primary reason for not going beyond programmatic statements and rather unsophisticated uses of fuzzy set theory has been the lack of practical methods for combining fuzzy set concepts with statistical methods. This monograph takes that topic as its major focus, and provides explicit guides for researchers who would like to harness fuzzy set concepts while being able to make statistical inferences and test their models. Real examples and data-sets from several disciplines illustrate the techniques and applications, demonstrating how a combination of fuzzy sets and statistics enable researchers to analyze their data in new ways.
The modern origin of fuzzy sets, fuzzy algebra, fuzzy decision making, and “computing with words” is conventionally traced to Lotfi Zadeh’s publication in 1965 of his path-breaking refutation of binary set theory. In a sixteen-page article, modestly titled “Fuzzy Sets” and published in the journal Information and Control, Zadeh launched a multi-disciplinary revolution. The start was relatively slow, but momentum gathered quickly. From 1970 to 1979 there were about 500 journal publications with the word fuzzy in the title; from 2000 to 2009 there were more than 35,000. At present, citations to Zadeh’s publications are running at a rate of about 1,500-2,000 per year, and this rate continues to rise. Almost all applications of Zadeh’s ideas have been in highly technical scientific fields, not in the social sciences. Zadeh was surprised by this development. In a personal note he states: “When I wrote my l965 paper, I expected that fuzzy set theory would be applied primarily in the realm of human sciences. Contrary to my expectation, fuzzy set theory and fuzzy logic are applied in the main in physical and engineering sciences.” In fact, the first comprehensive examination of fuzzy sets by a social scientist did not appear until 1987, a full twenty-two years after the publication of Zadeh’s seminal article, when Michael Smithson, an Australian psychologist, published Fuzzy Set Analysis for Behavioral and Social Sciences.
This new addition to the Applied Social Research Methods series is unrivalled, it is written by leaders in the growing field of rigorous, comparative techniques.
This volume brings together advanced thinking on the multidimensional measurement of poverty. This includes the theoretical background, applications to cross-sections using contemporary European examples, and longitudinal aspects of multidimensional fuzzy poverty analysis that pay particular attention to the transitory, or impermanent, conditions that often occur during transitions to market economies. The research is up-to-date and international.
Constructing Social Research answers the question: What is social science? Updated throughout with new references and examples, the Third Edition of this innovative text by Charles C. Ragin and Lisa M. Amoroso shows the unity within the diversity of activities called social research to help students understand how all social researchers construct representations of social life using theories, systematic data collection, and careful examination of that data.
Charles C. Ragin’s The Comparative Method proposes a synthetic strategy, based on an application of Boolean algebra, that combines the strengths of both qualitative and quantitative sociology. Elegantly accessible and germane to the work of all the social sciences, and now updated with a new introduction, this book will continue to garner interest, debate, and praise.