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How Judges Judge

Authors: Yung, Corey Rayburn;

How Judges Judge

Abstract

Full-text available at SSRN. See link in this record. ; This Article offers a new approach to understanding judicial behavior which recognizes judicial heterogeneity, behavior along different dimensions, and interconnectedness among judges at different levels within the judiciary. As a result, it calls into question those fundamental premises of the predominant theories of judicial decisionmaking utilized by legal and political science scholars. This study utilizes a unique dataset of over 30,000 judicial votes from eleven federal courts of appeals in 2008. Utilizing independent measures of judicial activism, ideology, independence, and partisanship, statistical cluster analysis identifies nine distinct judging styles: Trailblazing, Consensus Building, Stalwart, Regulating, Steadfast, Collegial, Incrementalist, Minimalist, and Error Correcting. These judicial style types offer a fuller and more accurate account of judicial behavior than any of the prior models utilized by scholars.

Country
United States
Related Organizations
Keywords

Courts of appeals, 340, Models, Decisionmaking, Federal courts, Judges, Law and courts, 320, Empirical

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
Green