Chicago-Kent College of Law

About: Chicago-Kent College of Law is a education organization based out in Chicago, Illinois, United States. It is known for research contribution in the topics: Supreme court & Comparative law. The organization has 101 authors who have published 563 publications receiving 5671 citations. The organization is also known as: IIT Chicago-Kent College of Law.

Genetic discrimination and health insurance: an urgent need for reform.

Abstract: The accelerated pace of gene discovery and molecular medicine portend a future in which information about a plethora of disease genes can be readily obtained. As at-risk populations are identified, research can be done to determine effective prevention and treatment strategies that will lower the personal, social and perhaps the financial costs of disease in the future. We all carry genes that predispose to common illnesses. In many circumstances knowing this information can be beneficial, as it allows individualized strategies to be designed to reduce the risk of illness. But, as knowledge about the genetic basis of common disorders grows, so does the potential for discrimination in health insurance coverage for an ever increasing number of Americans.

Predicting the Behavior of the Supreme Court of the United States: A General Approach.

Abstract: Building upon developments in theoretical and applied machine learning, as well as the efforts of various scholars including Guimera and Sales-Pardo (2011), Ruger et al. (2004), and Martin et al. (2004), we construct a model designed to predict the voting behavior of the Supreme Court of the United States. Using the extremely randomized tree method first proposed in Geurts, et al. (2006), a method similar to the random forest approach developed in Breiman (2001), as well as novel feature engineering, we predict more than sixty years of decisions by the Supreme Court of the United States (1953-2013). Using only data available prior to the date of decision, our model correctly identifies 69.7% of the Court’s overall affirm/reverse decisions and correctly forecasts 70.9% of the votes of individual justices across 7,700 cases and more than 68,000 justice votes. Our performance is consistent with the general level of prediction offered by prior scholars. However, our model is distinctive as it is the first robust, generalized, and fully predictive model of Supreme Court voting behavior offered to date. Our model predicts six decades of behavior of thirty Justices appointed by thirteen Presidents. With a more sound methodological foundation, our results represent a major advance for the science of quantitative legal prediction and portend a range of other potential applications, such as those described in Katz (2013).

A General Approach for Predicting the Behavior of the Supreme Court of the United States

Abstract: 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 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.

Constitutionalizing the Economy: German Neo-Liberalism, Competition Law and the 'New' Europe

Abstract: Despite its enormous importance in the evolution of competition law in Europe, ordoliberal thought — and German neo-liberal thought generally — has received little attention in the English-speaking world, and it remains all but unknown in the United States. Moreover, except in Germany, awareness of these ideas has been confined almost exclusively to economists, while lawyers and political scientists have seldom been exposed to them. Finally, there has been little modern study of the impact of these ideas on the development of European thought.In this article I address this critically important gap in our understanding of European thought and institutions. I seek to contribute to a fuller understanding of ordoliberal thought, particularly among non-German readers and among lawyers and policy analysts — to whom (together with economists) this body of thought has been addressed. In addition, I sketch the roles these ideas have played in the evolution of German and European legal thought and institutions, in general, and competition law, in particular.