Evidence-based sentencing and the scientific rationalization of discrimination.

• Author: Starr, Sonja B.
• Position: Introduction through II. The Disparate Treatment Concern, p. 803-841

INTRODUCTION I. ACTUARIAL RISK PREDICTION AND THE MOVEMENT TOWARD EVIDENCE BASED SENTENCING A. The Actuarial Instruments B. The Arguments for Evidence-Based Sentencing C. Scholarly Criticisms II. THE DISPARATE TREATMENT CONCERN A. Equal Protection 1. Gender classifications and the problem with statistical discrimination 2. Wealth-related classifications in the criminal justice system B. The Social Harm of Demographic and Socioeconomic Sentencing Discrimination III. ASSESSING THE EVIDENCE FOR EVIDENCE-BASED SENTENCING A. Precision, Group Averages, and Individual Predictions B. Do the Instruments Outperform Clinical Prediction and Other Alternatives C. Do the Risk Prediction Instruments Address the Right Question? IV. WILL RISK PREDICTION INSTRUMENTS REALLY CHANGE SENTENCING PRACTICE? A. Do the Instruments Merely Provide Information? B. Does Evidence-Based Sentencing Merely Replace One Form of Risk Prediction with Another? CONCLUSION INTRODUCTION

Providing equal justice for poor and rich, weak and powerful alike is an age-old problem. People have never ceased to hope and strive to move closer to that goal.... In this tradition, our own constitutional guaranties of due process and equal protection both call for procedures in criminal trials which allow no invidious discriminations .... [T]he central aim of our entire judicial system [is that] all people charged with crime must, so far as the law is concerned, "stand on an equality before the bar of justice in every American court."

--Justice Hugo Black, Griffin v. Illinois (1956) (1)

Criminal justice reformers have long worked toward a system in which defendants' treatment does not depend on their socioeconomic status or demographics but on their criminal conduct. How to achieve that objective is a complicated and disputed question. Many readers might assume, however, that there is at least a general consensus on some key "don'ts." For example, judges should not systematically sentence defendants more harshly because they are poor or uneducated, or more lightly because they are wealthy and educated. They should not follow a policy of increasing the sentences of male defendants, or reducing those of females, on the explicit basis of gender. They likewise should not increase a defendant's sentence specifically because she grew up without a stable, intact family or because she lives in a disadvantaged and crime-ridden community.

It might surprise many readers, then, to learn that a growing number of U.S. jurisdictions are adopting policies that deliberately encourage judges to do all of these "don'ts." These jurisdictions are directing sentencing judges to explicitly consider a variety of variables that often include socioeconomic status, gender, age, family, and neighborhood characteristics--not just in special contexts in which one of those variables might be particularly relevant (for instance, ability to pay in cases involving fines), but routinely, in all cases. This is not a fringe development. Courts in at least twenty states are already implementing some form of it. (2) One state supreme court has already enthusiastically endorsed it. (3) And it now has been embraced by the American Law Institute in the draft of the newly revised Model Penal Code (4)--a development that reflects its mainstream acceptance and may soon augur much more widespread adoption. There is a similar trend in Canada, the United Kingdom, and other foreign jurisdictions. (5) Meanwhile, the majority of states now similarly direct parole boards to consider demographic and socioeconomic factors. (6) This Article critiques this new trend on constitutional and policy grounds.

The trend is called "evidence-based sentencing" (EBS). "Evidence," in this formulation, refers not to the evidence in the particular case but to empirical research on factors predicting criminal recidivism. Based on that research, EBS provides sentencing judges with risk scores for each defendant based on variables that, in addition to criminal history, often include gender, age, marital status, and socioeconomic factors such as employment and education. EBS has been widely hailed by judges, advocates, and scholars as representing hope for a new age of scientifically guided sentencing. (7) Incongruously, this trend is being pushed by progressive reform advocates who hope it will reduce incarceration rates by enabling courts to identify low-risk offenders. In this Article, I argue that they are making a mistake. As currently practiced, EBS should be seen neither as progressive nor as especially scientific--and it is almost surely unconstitutional.

This Article sets forth a constitutional, methodological, and policy case against this approach, based on analysis of both the relevant doctrine and the empirical research supporting EBS. I show that several of the variables that many of the instruments use raise serious constitutional and normative concerns, and I review the empirical literature to show that the instruments do not advance state interests sufficiently to overcome those concerns. The concept of "evidence-based practice" is broad, and I do not mean to issue a sweeping indictment of all its many criminal justice applications. Indeed, I strongly endorse the objective of informing criminal justice policy generally, and sentencing specifically, with data. My objection is specifically to the use of demographic, socioeconomic, family, and neighborhood variables to determine whether and for how long a defendant is incarcerated. I focus principally on the instruments' use in sentencing, but virtually the same case can be made against their use in parole decisions.

The technocratic framing of EBS should not obscure an inescapable truth: sentencing based on such instruments amounts to overt discrimination based on demographics and socioeconomic status. The instruments' use of gender and socioeconomic variables, in particular, raises serious constitutional concerns, and yet, surprisingly, no existing scholarship sets forth the constitutional case against this practice. Gender is the only equal protection issue the existing literature pays any attention to, but those who have discussed it have reached the wrong conclusions, as I show here. I also show that the socioeconomic variables raise equally serious concerns under a line of Supreme Court doctrine concerning indigent criminal defendants, and in fact the Court has specifically condemned the notion of treating poverty as a predictor of recidivism risk.

Beyond the constitutional concerns, the use of these and other variables, such as family and neighborhood characteristics, is also troubling on policy grounds. Equal treatment of all persons is a central objective of the criminal justice system, and EBS as currently practiced may have serious social consequences. It can be expected to contribute to the concentration of the criminal justice system's punitive impact among those who already disproportionately bear its brunt, including people of color. And the expressive message of this approach to sentencing is, when stripped of the anodyne scientific language, toxic. Group-based generalizations about dangerousness have an insidious history in our culture, and the express embrace of additional punishment for the poor conveys the message that the system is rigged.

To be sure, the state has an important (even compelling) interest in reducing crime without unduly increasing incarceration. But contrary to other commentators, 1 do not think this interest can justify the use of demographic and socioeconomic variables in EBS. A careful review of the empirical evidence and methods underlying the instruments shows that their use does not substantially advance the state's penological interests and that less discriminatory alternatives would likely perform at least as well. This is true for three major reasons.

First, the instruments provide nothing close to precise predictions of individual recidivism risk. The underlying regression models may provide reasonably precise estimates of the average recidivism rates for the group of offenders sharing the defendant's characteristics, but the uncertainty about what an individual offender will do is much greater, and when it comes to predicting individual behavior, the models offer fairly modest improvements over chance. While EBS literature sometimes acknowledges this limitation, most advocates have downplayed its seriousness, and existing scholarship has not recognized its legal import. The individual prediction problem is constitutionally important because the Supreme Court's cases on gender and indigent defendants have consistently held that disparate treatment cannot be justified based on statistical generalizations about group tendencies, even if they are empirically supported. Rather, individuals are entitled to be treated as individuals.

Second, there is no persuasive evidence that the instruments' predictive power exceeds that of either the current system (in which judges use their individual "clinical" judgment to assess risk) or less discriminatory alternative instruments. A core EBS premise, ubiquitously repeated, is that actuarial risk prediction consistently outperforms "clinical" predictions. (8) I examine the literature on which that claim is based and find it unsupportive of this generalization. Instead, it shows that the specifics of the actuarial instrument matter--and the few comparative studies that specifically involve recidivism prediction have had mixed results and largely involve instruments that do not look much like the ones actually being used in sentencing. The literature also indicates that the constitutionally problematic variables add little marginal predictive power, suggesting the alternative of instruments that do not include those variables

Third, even if the instruments predicted individual recidivism perfectly, they do not even attempt to predict the thing that judges need to know to use...