12,558 research outputs found
A General Approach for Predicting the Behavior of the Supreme Court of the United States
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 which leverages
some 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 70.2% accuracy at the case outcome level
and 71.9% at the justice vote level. More recently, over the past century, we
outperform an in-sample optimized null model by nearly 5%. Our performance is
consistent with, and improves on the general level of prediction demonstrated
by prior work; however, our model is distinctive because it can be applied
out-of-sample to the entire past and future of the Court, not a single term.
Our results represent an important advance for the science of quantitative
legal prediction and portend a range of other potential applications.Comment: version 2.02; 18 pages, 5 figures. This paper is related to but
distinct from arXiv:1407.6333, and the results herein supersede
arXiv:1407.6333. Source code available at
https://github.com/mjbommar/scotus-predict-v
Curriculum Guidelines for Undergraduate Programs in Data Science
The Park City Math Institute (PCMI) 2016 Summer Undergraduate Faculty Program
met for the purpose of composing guidelines for undergraduate programs in Data
Science. The group consisted of 25 undergraduate faculty from a variety of
institutions in the U.S., primarily from the disciplines of mathematics,
statistics and computer science. These guidelines are meant to provide some
structure for institutions planning for or revising a major in Data Science
Aerospace medicine and biology: A continuing bibliography with indexes (supplement 323)
This bibliography lists 125 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during April, 1989. Subject coverage includes; aerospace medicine and psychology, life support systems and controlled environments, safety equipment exobiology and extraterrestrial life, and flight crew behavior and performance
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