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Valence and interactions in judicial voting.

Published version
Peer-reviewed

Repository DOI


Change log

Authors

Cantwell, George T 

Abstract

The collective statistics of voting on judicial courts present hints about their inner workings. Many approaches for studying these statistics, however, assume that judges' decisions are conditionally independent: a judge reaches a decision based on the case at hand and his or her personal views. In reality, judges interact. We develop a minimal model that accounts for judge bias, depending on the context of the case, and peer interaction. We apply the model to voting data from the US Supreme Court. We find strong evidence that interaction is an important factor across natural courts from 1946 to 2021. We also find that, after accounting for interaction, the recovered biases differ from highly cited ideological scores. Our method exemplifies how physics and complexity-inspired modelling can drive the development of theoretical models and improved measures for political voting. This article is part of the theme issue 'A complexity science approach to law and governance'.

Description

Peer reviewed: True


Publication status: Published

Keywords

US Supreme Court, bias, group interactions, maximum entropy, statistical inference, voting

Journal Title

Philos Trans A Math Phys Eng Sci

Conference Name

Journal ISSN

1364-503X
1471-2962

Volume Title

382

Publisher

The Royal Society
Sponsorship
Division of Computing and Communication Foundations (BIGDATA-1838251)
Austrian Science Fund (ESP 127-N)