D
Daniel Martin Katz
Researcher at Chicago-Kent College of Law
Publications - 84
Citations - 1663
Daniel Martin Katz is an academic researcher from Chicago-Kent College of Law. The author has contributed to research in topics: Supreme court & Computer science. The author has an hindex of 20, co-authored 77 publications receiving 1215 citations. Previous affiliations of Daniel Martin Katz include Stanford University & Georgia State University.
Papers
More filters
Journal ArticleDOI
A Systematic Review of Serious Games in Training Health Care Professionals.
TL;DR: This systematic review aimed to synthesize current serious gaming trends in health care training, especially those pertaining to developmental methodologies and game evaluation, to create schemas that organize how educators approach their development and evaluation.
Journal ArticleDOI
Predicting the Behavior of the Supreme Court of the United States: A General Approach.
TL;DR: 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 and outperforms null models at both the justice and case level under both parametric and non-parametric tests.
Journal ArticleDOI
A General Approach for Predicting the Behavior of the Supreme Court of the United States
Daniel Martin Katz,Daniel Martin Katz,Michael James Bommarito,Michael James Bommarito,Josh Blackman +4 more
TL;DR: The authors used 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).
Posted Content
Quantitative Legal Prediction – or – How I Learned to Stop Worrying and Start Preparing for the Data Driven Future of the Legal Services Industry
TL;DR: In this paper, the authors highlight the coming age of Quantitative Legal Prediction with hopes that practicing lawyers, law students and law schools will take heed and prepare to survive (thrive) in this new ordering.
Posted Content
Predicting the Behavior of the Supreme Court of the United States: A General Approach
TL;DR: The model is distinctive as it is the first robust, generalized, and fully predictive model of Supreme Court voting behavior offered to date and represents a major advance for the science of quantitative legal prediction.