Punishing on a Curve

Abstract

Does the punishment of one defendant change because of how she fares in comparison to the other defendants on the judge’s docket? This article demonstrates that the troubling answer is yes. Judges sentence the same case more harshly when their caseloads contain relatively milder offenses, and more leniently when their caseloads contain more serious crimes. I call this problem “punishing on a curve.”Consequently, the article shows how such relative sentencing patterns put into question the prevailing practice of establishing specialized courts or courts of limited jurisdiction. Because judges are punishing on a curve, the court’s jurisdiction systematically shapes sentencing outcomes. Courts of limited jurisdiction usually specialize in relatively less serious crimes (such as misdemeanors, drug offenses, or juvenile cases). They treat the mild offenses on their docket more harshly than generalist courts, that also see severe crimes, would have treated them. This leads to the disturbing effect of increasing punitive outcomes vis-a-vis these offenses, wholly contradictory to the missions of these courts. Such sentencing patterns undermine notions of justice and equitable treatment. They also undermine retributive principles and marginal deterrence across crimes of increasing severity.In light of the profound normative and practical implications, the article offers a remedy to standardize sentences through “statistical curving.” In addition to consulting the sentencing range recommended by the sentencing guidelines for a particular offense, a judge should see the distribution of sentences for the same offense across different courts. The article illustrates the feasibility of the proposal empirically using sentencing data from neighboring judicial districts in Pennsylvania. It also explains how this proposal fits within the Supreme Court’s jurisprudence following United States v. Booker, which rendered the sentencing guidelines advisory, and its potential advantage in improving appellate review.