Arraignment

Abstract: "That relatively few criminal cases in this country are resolved by full Perry Mason-style strials is fairly common knowledge. Most cases are settled by a guilty plea after some form of negotiation over the charge or sentence. But why? The standard explanation is case pressure: the enormous volume of criminal cases, to be processed with limited staff, time and resources. . . . But a large body of new empirical research now demands that we re-examine plea negotiation. Milton Heumann's book, "Plea Bargaining, " strongly and explicitly attacks the case-pressure argument and suggests an alternative explanation for plea bargaining based on the adaptation of attorneys and judges to the local criminal court. The book is a significant and welcome addition to the literature. Heumann's investigation of case pressure and plea negotiation demonstrates solid research and careful analysis."-"Michigan Law Review"

Abstract: Arguably the most important decision at an arraignment is whether to release an offender until the date of his or her next scheduled court appearance. Under the Bail Reform Act of 1984, threats to public safety can be a key factor in that decision. Implicitly, a forecast of “future dangerousness” is required. In this article, we consider in particular whether usefully accurate forecasts of domestic violence can be obtained. We apply machine learning to data on over 28,000 arraignment cases from a major metropolitan area in which an offender faces domestic violence charges. One of three possible post-arraignment outcomes is forecasted within two years: (1) a domestic violence arrest associated with a physical injury, (2) a domestic violence arrest not associated with a physical injury, and (3) no arrests for domestic violence. We incorporate asymmetric costs for different kinds of forecasting errors so that very strong statistical evidence is required before an offender is forecasted to be a good risk. When an out-of-sample forecast of no post-arraignment domestic violence arrests within two years is made, it is correct about 90 percent of the time. Under current practice within the jurisdiction studied, approximately 20 percent of those released after an arraignment for domestic violence are arrested within two years for a new domestic violence offense. If magistrates used the methods we have developed and released only offenders forecasted not to be arrested for domestic violence within two years after an arraignment, as few as 10 percent might be arrested. The failure rate could be cut nearly in half. Over a typical 24-month period in the jurisdiction studied, well over 2,000 post-arraignment arrests for domestic violence perhaps could be averted.

Abstract: In the United States, roughly 450,000 people are detained awaiting trial on any given day, typically because they have not posted bail. Using a large sample of criminal cases in Philadelphia and Pittsburgh, we analyze the consequences of the money bail system by exploiting the variation in bail-setting tendencies among randomly assigned bail judges. Our estimates suggest that the assignment of money bail causes a 12% rise in the likelihood of conviction, and a 6-9% rise in recidivism. Our results highlight the importance of credit constraints in shaping defendant outcomes and point to important fairness considerations in the institutional design of the American money bail system.