Against the backdrop of an explosion of interest in new techniques for data collection and theory testing, this volume provides a fresh programmatic statement about comparative-historical analysis. It examines the advances and distinctive contributions that CHA has made to theory generation and the explanation of large-scale outcomes that newer approaches often regard as empirically intractable. An introductory essay locates the sources of CHA's enduring influence in core characteristics that distinguish this approach, such as its attention to process and its commitment to empirically grounded, deep case-based research. Subsequent chapters explore broad research programs inspired by CHA work, new analytic tools for studying temporal processes and institutional dynamics, and recent methodological tools for analyzing sequences and for combining CHA work with other approaches. This volume is essential reading for scholars seeking to learn about the sources of CHA's enduring influence and
Social media has put mass communication in the hands of normal people on an unprecedented scale, and has also given social scientists the tools necessary to listen to the voices of everyday people around the world. This book gives social scientists the skills necessary to leverage that opportunity, and transform social media's vast stream of information into social science data. The book combines the big data techniques of computer science with social science methodology. Intended as a text for advanced undergraduates, graduate students, and researchers in the social sciences, this book provides a methodological pathway for scholars who want to make use of this new and evolving source of data. It provides a framework for building one's own data collection and analysis infrastructure, a toolkit of content analysis, geographic analysis, and network analysis, and meditations on the ethical implications of social media data.
Social media has put mass communication in the hands of normal people on an unprecedented scale, and has also given social scientists the tools necessary to listen to the voices of everyday people around the world. This book gives social scientists the skills necessary to leverage that opportunity, and transform social media's vast stream of information into social science data. The book combines the big data techniques of computer science with social science methodology. Intended as a text for advanced undergraduates, graduate students, and researchers in the social sciences, this book provides a methodological pathway for scholars who want to make use of this new and evolving source of data. It provides a framework for building one's own data collection and analysis infrastructure, a toolkit of content analysis, geographic analysis, and network analysis, and meditations on the ethical implications of social media data.
John Gerring's exceptional textbook has been thoroughly revised in this second edition. It offers a one-volume introduction to social science methodology relevant to the disciplines of anthropology, economics, history, political science, psychology and sociology. This new edition has been extensively developed with the introduction of new material and a thorough treatment of essential elements such as conceptualization, measurement, causality and research design. It is written for students, long-time practitioners and methodologists and covers both qualitative and quantitative methods. It synthesizes the vast and diverse field of methodology in a way that is clear, concise and comprehensive. While offering a handy overview of the subject, the book is also an argument about how we should conceptualize methodological problems. Thinking about methodology through this lens provides a new framework for understanding work in the social sciences.
John Gerring's exceptional textbook has been thoroughly revised in this second edition. It offers a one-volume introduction to social science methodology relevant to the disciplines of anthropology, economics, history, political science, psychology and sociology. This new edition has been extensively developed with the introduction of new material and a thorough treatment of essential elements such as conceptualization, measurement, causality and research design. It is written for students, long-time practitioners and methodologists and covers both qualitative and quantitative methods. It synthesizes the vast and diverse field of methodology in a way that is clear, concise and comprehensive. While offering a handy overview of the subject, the book is also an argument about how we should conceptualize methodological problems. Thinking about methodology through this lens provides a new framework for understanding work in the social sciences.
Democratization and Research Methods is a coherent survey and critique of both democratization research and the methodology of comparative politics. The two themes enhance each other: the democratization literature illustrates the advantages and disadvantages of various methodological approaches, and the critique of methods makes sense of the vast and bewildering democratization field. Michael Coppedge argues that each of the three main approaches in comparative politics - case studies and comparative histories, formal modeling and large-sample statistical analysis - accomplishes one fundamental research goal relatively well: 'thickness', integration and generalization, respectively. Throughout the book, comprehensive surveys of democratization research demonstrate that each approach accomplishes one of these goals well but the other two poorly. Chapters cover conceptualization and measurement, case studies and comparative histories, formal models and theories, political culture and su
Democratization and Research Methods is a coherent survey and critique of both democratization research and the methodology of comparative politics. The two themes enhance each other: the democratization literature illustrates the advantages and disadvantages of various methodological approaches, and the critique of methods makes sense of the vast and bewildering democratization field. Michael Coppedge argues that each of the three main approaches in comparative politics - case studies and comparative histories, formal modeling and large-sample statistical analysis - accomplishes one fundamental research goal relatively well: 'thickness', integration and generalization, respectively. Throughout the book, comprehensive surveys of democratization research demonstrate that each approach accomplishes one of these goals well but the other two poorly. Chapters cover conceptualization and measurement, case studies and comparative histories, formal models and theories, political culture and su
Reflecting the rising popularity of research that combines qualitative and quantitative social science, Multi-Method Social Science provides the first systematic guide to designing multi-method research. It argues that methods can be productively combined using the framework of integrative multi-method research, with one method used to carry out a final causal inference, and methods from other traditions used to test the key assumptions involved in that causal inference. In making this argument, Jason Seawright considers a wide range of statistical tools including regression, matching, and natural experiments. The book also discusses qualitative tools including process tracing, the use of causal process observations, and comparative case study research. Along the way, the text develops over a dozen multi-method designs to test key assumptions about social science causation.
Social scientists have identified a need to move beyond the analysis of correlation among variables to the study of causal mechanisms that link them. Nicholas Weller and Jeb Barnes propose that a solution lies in 'pathway analysis', the use of case studies to explore the causal links between related variables. This book focuses on how the small-N component of multi-method research can meaningfully contribute and add value to the study of causal mechanisms. The authors present both an extended rationale for the unique role that case studies can play in causal mechanism research, and a detailed view of the types of knowledge that case studies should try to generate and how to leverage existing large-N data to guide the case selection process. The authors explain how to use their approach both to select cases and to provide context on previously studied cases.
Social scientists have identified a need to move beyond the analysis of correlation among variables to the study of causal mechanisms that link them. Nicholas Weller and Jeb Barnes propose that a solution lies in 'pathway analysis', the use of case studies to explore the causal links between related variables. This book focuses on how the small-N component of multi-method research can meaningfully contribute and add value to the study of causal mechanisms. The authors present both an extended rationale for the unique role that case studies can play in causal mechanism research, and a detailed view of the types of knowledge that case studies should try to generate and how to leverage existing large-N data to guide the case selection process. The authors explain how to use their approach both to select cases and to provide context on previously studied cases.
Case Study Research: Principles and Practices provides a general understanding of the case study method as well as specific tools for its successful implementation. These tools are applicable in a variety of fields including anthropology, business and management, communications, economics, education, medicine, political science, psychology, social work, and sociology. Topics include: a survey of case study approaches; a methodologically tractable definition of 'case study'; strategies for case selection, including random sampling and other algorithmic approaches; quantitative and qualitative modes of case study analysis; and problems of internal and external validity. The second edition of this core textbook is designed to be accessible to readers who are new to the subject and is thoroughly revised and updated, incorporating recent research, numerous up-to-date studies and comprehensive lecture slides.
Case Study Research: Principles and Practices provides a general understanding of the case study method as well as specific tools for its successful implementation. These tools are applicable in a variety of fields including anthropology, business and management, communications, economics, education, medicine, political science, psychology, social work, and sociology. Topics include: a survey of case study approaches; a methodologically tractable definition of 'case study'; strategies for case selection, including random sampling and other algorithmic approaches; quantitative and qualitative modes of case study analysis; and problems of internal and external validity. The second edition of this core textbook is designed to be accessible to readers who are new to the subject and is thoroughly revised and updated, incorporating recent research, numerous up-to-date studies and comprehensive lecture slides.
Reflecting the rising popularity of research that combines qualitative and quantitative social science, Multi-Method Social Science provides the first systematic guide to designing multi-method research. It argues that methods can be productively combined using the framework of integrative multi-method research, with one method used to carry out a final causal inference, and methods from other traditions used to test the key assumptions involved in that causal inference. In making this argument, Jason Seawright considers a wide range of statistical tools including regression, matching, and natural experiments. The book also discusses qualitative tools including process tracing, the use of causal process observations, and comparative case study research. Along the way, the text develops over a dozen multi-method designs to test key assumptions about social science causation.
Fairfield and Charman provide a modern, rigorous and intuitive methodology for case-study research to help social scientists and analysts make better inferences from qualitative evidence. The book develops concrete guidelines for conducting inference to best explanation given incomplete information; no previous exposure to Bayesian analysis or specialized mathematical skills are needed. Topics covered include constructing rival hypotheses that are neither too simple nor overly complex, assessing the inferential weight of evidence, counteracting cognitive biases, selecting cases, and iterating between theory development, data collection, and analysis. Extensive worked examples apply Bayesian guidelines, showcasing both exemplars of intuitive Bayesian reasoning and departures from Bayesian principles in published case studies drawn from process-tracing, comparative, and multimethod research. Beyond improving inference and analytic transparency, an overarching goal of this book is to
This book seeks to narrow two gaps: first, between the widespread use of case studies and their frequently 'loose' methodological moorings; and second, between the scholarly community advancing methodological frontiers in case study research and the users of case studies in development policy and practice. It draws on the contributors' collective experience at this nexus, but the underlying issues are more broadly relevant to case study researchers and practitioners in all fields. How does one prepare a rigorous case study? When can causal inferences reasonably be drawn from a single case? When and how can policy-makers reasonably presume that a demonstrably successful intervention in one context might generate similarly impressive outcomes elsewhere, or if massively 'scaled up'? No matter their different starting points – disciplinary base, epistemological orientation, sectoral specialization, or practical concerns – readers will find issues of significance for their own field, and
This book seeks to narrow two gaps: first, between the widespread use of case studies and their frequently 'loose' methodological moorings; and second, between the scholarly community advancing methodological frontiers in case study research and the users of case studies in development policy and practice. It draws on the contributors' collective experience at this nexus, but the underlying issues are more broadly relevant to case study researchers and practitioners in all fields. How does one prepare a rigorous case study? When can causal inferences reasonably be drawn from a single case? When and how can policy-makers reasonably presume that a demonstrably successful intervention in one context might generate similarly impressive outcomes elsewhere, or if massively 'scaled up'? No matter their different starting points – disciplinary base, epistemological orientation, sectoral specialization, or practical concerns – readers will find issues of significance for their own field, and
