Articlegreen2004

Competing Approaches to Predicting Supreme Court Decision Making

Andrew D. Martin · Kevin M. Quinn · Theodore W. Ruger · Pauline T. Kim

133 citations0/0 files storedPerspectives on Politics

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Judicial and Constitutional Studies Electoral Systems and Political Participation American Constitutional Law and Politics

Abstract

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.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 133 citations exist upstream.

References

1974Why the “Haves” Come Out Ahead: Speculations on the Limits of Legal Change 1935The Logic of Inductive Inference 2002Dynamic Ideal Point Estimation via Markov Chain Monte Carlo for the U.S. Supreme Court, 1953–1999 1935124: The Logic of Inductive Inference.1991Patterns of Congressional Voting 1992Anatomy of an Experimental Political Stock Market 1988The Ideological Effects of Actuarial Practices 2004The Supreme Court Forecasting Project: Legal and Political Science Approaches to Predicting Supreme Court Decisionmaking

Cited by

2012Improving Predictions using Ensemble Bayesian Model Averaging 2015Trusting Judgements: How to Get the Best out of Experts 2021Natural language processing in law: Prediction of outcomes in the higher courts of Turkey 2011Emotions, Oral Arguments, and Supreme Court Decision Making 2020Predicting Outcomes of Legal Cases based on Legal Factors using Classifiers 2020Legal Judgement Prediction for UK Courts

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.