Article I, Section 4 of the Constitution, the Voting Rights Act, and Restoration of the Congressional Portion of the Election Ballot: The Final Frontier of Felon Disenfranchisement Jurisprudence?

Article published in the Journal of Law and Social Change

Institutional Rules, Strategic Behavior and the Legacy of Chief Justice William Rehnquist: Setting the Record Straight on Dickerson v. United States

Why did Justice Rehnquist behave the way he did in Dickerson v. United States? As written, many prevailing accounts accept Justice Rehnquist\u27s opinion in Dickerson v. United States at face value and disavow the potential of a strategic explanation. The difficulty with the non-strategic accounts is their failure to outline explicitly the evidence supporting the uniqueness of their theory. Specifically, these explanations largely ignore the alternative set of preferences which could have produced the Chief\u27s decision. This is troubling because prior scholarship demonstrates that a chief justice possesses a unique set of institutional powers which provides significant incentive for him to behave sophisticatedly. Many prevailing explanations for Dickerson at a minimum are incomplete because they fail to determine whether his vote and opinion were the result of moderation, fidelity to traditional legal principles, or, in fact, strategic behavior. This article pursues a uniqueness claim, arguing the gravamen of available evidence supports a strategic explanation for Justice Rehnquist\u27s behavior in Dickerson. To do this, the article first reviews the methodological debate which exists within the social science scholarship, a debate relevant to the competing explanations for the Dickerson decision. Next, the article explores the strategic or quasi-game theoretic approach by describing the multistage sophisticated process which produces all Supreme Court decisions. It culminates in Figure 1.1, a general diagram that is carried forward into Part II of the article. Part II directly considers the Dickerson decision. This section begins with a description of the Supreme Court\u27s Miranda jurisprudence before reviewing the specific facts and procedural history of the case. Next, Part II reviews Justice Rehnquist\u27s Miranda-related decisions which, taken together, demonstrate the truly anomalous nature of the Dickerson opinion. The article then outlines its strategic account, an approach rejecting many prevailing explanations of Rehnquist\u27s behavior. Strategic and non-strategic behaviors are often observationally equivalent. Thus, in order firmly to support its strategic theory, this article concludes with a discussion of several important post-Dickerson decisions including Chavez v. Martinez, Missouri v. Seibert, and United States v. Patane, where the Chief Justice surprisingly supports the preservation of certain exceptions to Miranda even after his Dickerson opinion supposedly afforded Miranda full constitutional status. The cases are critical to the analysis because they help determine what end Chief Justice Rehnquist actually achieved in his Dickerson opinion. He successfully froze a set of pre-Dickerson Miranda exceptions which he personally developed during his thirty year tenure on the Court. It is from this perspective that commentators in fact are correct to argue that Dickerson is critical to understanding the legacy of the late Chief Justice

Quantitative Legal Prediction--or--How I Learned to Stop Worrying and Start Preparing for the Data-Driven Future of the Legal Services Industry

Welcome to law\u27s information revolution-revolution already in progress

On the Stability of Community Detection Algorithms on Longitudinal Citation Data

There are fundamental differences between citation networks and other classes of graphs. In particular, given that citation networks are directed and acyclic, methods developed primarily for use with undirected social network data may face obstacles. This is particularly true for the dynamic development of community structure in citation networks. Namely, it is neither clear when it is appropriate to employ existing community detection approaches nor is it clear how to choose among existing approaches. Using simulated data, we attempt to clarify the conditions under which one should use existing methods and which of these algorithms is appropriate in a given context. We hope this paper will serve as both a useful guidepost and an encouragement to those interested in the development of more targeted approaches for use with longitudinal citation data.Comment: 17 pages, 7 figures, presenting at Applications of Social Network Analysis 2009, ETH Zurich Edit, August 17, 2009: updated abstract, figures, text clarification

Complex Societies and the Growth of the Law

While a large number of informal factors influence how people interact, modern societies rely upon law as a primary mechanism to formally control human behaviour. How legal rules impact societal development depends on the interplay between two types of actors: the people who create the rules and the people to which the rules potentially apply. We hypothesise that an increasingly diverse and interconnected society might create increasingly diverse and interconnected rules, and assert that legal networks provide a useful lens through which to observe the interaction between law and society. To evaluate these propositions, we present a novel and generalizable model of statutory materials as multidimensional, time-evolving document networks. Applying this model to the federal legislation of the United States and Germany, we find impressive expansion in the size and complexity of laws over the past two and a half decades. We investigate the sources of this development using methods from network science and natural language processing. To allow for cross-country comparisons over time, we algorithmically reorganise the legislative materials of the United States and Germany into cluster families that reflect legal topics. This reorganisation reveals that the main driver behind the growth of the law in both jurisdictions is the expansion of the welfare state, backed by an expansion of the tax state.Comment: 22 pages, 6 figures (main paper); 28 pages, 11 figures (supplementary information

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