Search results for ""author gregory wawro""

Parliamentary obstruction, popularly known as the "filibuster," has been a defining feature of the U.S. Senate throughout its history. In this book, Gregory J. Wawro and Eric Schickler explain how the Senate managed to satisfy its lawmaking role during the nineteenth and early twentieth century, when it lacked seemingly essential formal rules for governing debate. What prevented the Senate from self-destructing during this time? The authors argue that in a system where filibusters played out as wars of attrition, the threat of rule changes prevented the institution from devolving into parliamentary chaos. They show that institutional patterns of behavior induced by inherited rules did not render Senate rules immune from fundamental changes. The authors' theoretical arguments are supported through a combination of extensive quantitative and case-study analysis, which spans a broad swath of history. They consider how changes in the larger institutional and political context--such as the expansion of the country and the move to direct election of senators--led to changes in the Senate regarding debate rules. They further investigate the impact these changes had on the functioning of the Senate. The book concludes with a discussion relating battles over obstruction in the Senate's past to recent conflicts over judicial nominations.

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How to study the past using dataQuantitative Analysis for Historical Social Science advances historical research in the social sciences by bridging the divide between qualitative and quantitative analysis. Gregory Wawro and Ira Katznelson argue for an expansion of the standard quantitative methodological toolkit with a set of innovative approaches that better capture nuances missed by more commonly used statistical methods. Demonstrating how to employ such promising tools, Wawro and Katznelson address the criticisms made by prominent historians and historically oriented social scientists regarding the shortcomings of mainstream quantitative approaches for studying the past.Traditional statistical methods have been inadequate in addressing temporality, periodicity, specificity, and context—features central to good historical analysis. To address these shortcomings, Wawro and Katznelson argue for the application of alternative approaches that are particularly well-suited to incorporating these features in empirical investigations. The authors demonstrate the advantages of these techniques with replications of research that locate structural breaks and uncover temporal evolution. They develop new practices for testing claims about path dependence in time-series data, and they discuss the promise and perils of using historical approaches to enhance causal inference.Opening a dialogue among traditional qualitative scholars and applied quantitative social scientists focusing on history, Quantitative Analysis for Historical Social Science illustrates powerful ways to move historical social science research forward.

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How to study the past using dataQuantitative Analysis for Historical Social Science advances historical research in the social sciences by bridging the divide between qualitative and quantitative analysis. Gregory Wawro and Ira Katznelson argue for an expansion of the standard quantitative methodological toolkit with a set of innovative approaches that better capture nuances missed by more commonly used statistical methods. Demonstrating how to employ such promising tools, Wawro and Katznelson address the criticisms made by prominent historians and historically oriented social scientists regarding the shortcomings of mainstream quantitative approaches for studying the past.Traditional statistical methods have been inadequate in addressing temporality, periodicity, specificity, and context—features central to good historical analysis. To address these shortcomings, Wawro and Katznelson argue for the application of alternative approaches that are particularly well-suited to incorporating these features in empirical investigations. The authors demonstrate the advantages of these techniques with replications of research that locate structural breaks and uncover temporal evolution. They develop new practices for testing claims about path dependence in time-series data, and they discuss the promise and perils of using historical approaches to enhance causal inference.Opening a dialogue among traditional qualitative scholars and applied quantitative social scientists focusing on history, Quantitative Analysis for Historical Social Science illustrates powerful ways to move historical social science research forward.

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