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Competing Approaches to Predicting Supreme Court Decision Making

Published online by Cambridge University Press:  01 December 2004

Andrew D. Martin
Affiliation:
Andrew D. Martin (admartin@wustl.edu) is associate professor of political science at Washington University, St. Louis
Kevin M. Quinn
Affiliation:
Kevin Quinn (kquinn@latte.harvard.edu) is assistant professor at Harvard University, Department of Government
Theodore W. Ruger
Affiliation:
Theodore W. Ruger (truger@law.upenn.edu) is assistant professor at the University of Pennsylvania Law School
Pauline T. Kim
Affiliation:
Pauline T. Kim (kim@wulaw.wustl.edu) is professor of law at Washington University School of Law

Extract

Political scientists and legal academics have long scrutinized the U.S. Supreme Court's work to understand what motivates the justices. Despite significant differences in methodology, both disciplines seek to explain the Court's decisions by focusing on examining past cases. This retrospective orientation is surprising. In other areas of government, for example, presidential elections and congressional decision making, political scientists engage in systematic efforts to predict outcomes, yet few have done this for court decisions. Legal academics, too, possess expertise that should enable them to forecast legal events with some accuracy. After all, the everyday practice of law requires lawyers to predict court decisions in order to advise clients or determine litigation strategies.The authors thank Michael Cherba, Nancy Cummings, David Dailey, Alison Garvey, Nick Hershman, and Robin Rimmer for their assistance. Their project is supported in part by National Science Foundation grants SES-0135855 and SES 0136679. The foundation bears no responsibility for the results or conclusions.

Type
SYMPOSIUM
Copyright
© 2004 American Political Science Association

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