Law Commons^™

A General Approach For Predicting The Behavior Of The Supreme Court Of The United States, Daniel Katz

All Faculty Scholarship

Building on developments in machine learning and prior work in the science of judicial prediction, we construct a model designed to predict the behavior of the Supreme Court of the United States in a generalized, out-of-sample context. To do so, we develop a time-evolving random forest classifier that leverages unique feature engineering to predict more than 240,000 justice votes and 28,000 cases outcomes over nearly two centuries (1816-2015). Using only data available prior to decision, our model outperforms null (baseline) models at both the justice and case level under both parametric and non-parametric tests. Over nearly two centuries, we achieve …

Will Quants Rule The (Legal) World?, Edward K. Cheng

Vanderbilt Law School Faculty Publications

Professor Ian Ayres, in his new book, Super Crunchers, details the brave new world of statistical prediction and how it has already begun to affect our lives. For years, academic researchers have known about the considerable and at times surprising advantages of statistical models over the considered judgments of experienced clinicians and experts. Today, these models are emerging all over the landscape. Whether the field is wine, baseball, medicine, or consumer relations, they are vying against traditional experts for control over how we make decisions. For the legal system, the take-home of Ayres's book and the examples he describes is …

Transport Modeling – Technical And Legal Issues, Adrian Brown

Uncovering the Hidden Resource: Groundwater Law, Hydrology, and Policy in the 1990s (Summer Conference, June 15-17)

27 pages.

Contains footnotes.