Predicting Supreme Court Behavior in Indian Law Cases

51 Pages Posted: 15 Jun 2018 Last revised: 18 Feb 2022

See all articles by Grant Christensen

Grant Christensen

Stetson University - College of Law

Date Written: January 1, 2021

Abstract

This piece builds upon Matthew Fletcher’s call for additional empirical work in Indian law by creating a new dataset of Indian law opinions. The piece takes every Indian law case decided by the Supreme Court from the beginning of the Warren Court until the end of the 2019-2020 term. The scholarship first produces an Indian law scorecard that measures how often each Justice voted for the “pro-Indian” outcome. It then compares those results to the Justice’s political ideology to suggest that while there is a general trend that a more “liberal” justice is more likely to favor the pro-Indian interest, that trend is generally weak with considerable variance from justice to justice. Finally, the article then creates a logistic regression model in order to try to predict whether a pro-Indian outcome is likely to prevail at the Court. It finds six potential variables to be statistically significant. It uses quantitative analysis to prove that the Indian interest is more likely to prevail when the Tribe is the appellant, when the issue is framed as a jurisdictional contest, and when the case arises from certain regions of the country. It suggests that Indian law advocates may use these insights to help influence litigation strategies in the future.

Keywords: Indian Law, Indigenous, Native American, Indian, Supreme Court, Solicitor General, Solicitor, State, Jurisdiction, Regression, Model, Prediction, Supreme Court behavior

Suggested Citation

Christensen, Grant, Predicting Supreme Court Behavior in Indian Law Cases (January 1, 2021). 26 Mich. J. Race & L. 65 (2001), Available at SSRN: https://ssrn.com/abstract=3197007 or http://dx.doi.org/10.2139/ssrn.3197007

Grant Christensen (Contact Author)

Stetson University - College of Law ( email )

1401 61st Street South
Gulfport, FL 33707
United States

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