Using group statistics to sentence individual criminals: an ethical and statistical critique of the Virginia risk assessment program.

AuthorNetter, Brian
  1. INTRODUCTION

    In an ideal crime-fighting world, we would know every convict's criminal proclivities. An offender could be detained for precisely the right amount of time as we effortlessly balanced the many competing interests served by our system of criminal justice. Of course, such a system would, of necessity, require invasions of civil liberties that even the toughest on crime might deem unreasonable. (1) Thus, our myriad schemes for criminal sentencing rely upon proxies to estimate how best to achieve the goals of "deterring crime, incapacitating the offender, providing just punishment, and rehabilitating the offender." (2)

    To enhance these proxies, considerable efforts have been devoted to developing tools to predict criminal behavior and criminological trends. (3) But these efforts fall far short of predictive accuracy. In light of these failings, there is a threshold ethical dilemma that we seldom consider: how good must predictive efforts be to justify using them to take restrictive actions that implicate the liberties of others?

    The Commonwealth of Virginia sits at the forefront of predictive techniques. Anticipating that prison space would become scarce after implementing a truth-in-sentencing initiative to extend sentences for violent crime, Virginia has spent a decade studying how to use its prison space efficiently to reduce future crime. The goal has been to divide nonviolent criminal offenders into groups--those deemed most likely to recidivate are imprisoned while those assessed to pose less of a threat to society are given alternative sanctions. (4) On its face, such a program seems pedestrian and unremarkable. After all, judges routinely make determinations about offender riskiness during sentencing hearings. (5) But Virginia chose not to rely on the expertise of judges for this initiative; instead, the Commonwealth commissioned a risk-assessment tool, based on a statistical study of recidivism, to make an initial division between the dangerous destined for prison and those others who could be welcomed back into society without visiting the state penitentiary. The system relies upon simple worksheets that tally demerits for past crimes with additional penalties for demographic characteristics found to be correlated with the commission of crime. Thus, a young, unemployed, never-married man is considerably more likely to face jail time than an older, divorced woman who held a job prior to committing an identical crime.

    The Virginia risk assessment program presents serious issues regarding the ethical propriety of predictive techniques in criminal sentencing. An evaluation of the program forces us to ask what classes of information we are comfortable considering when penalizing criminal misdeeds. Our answers to these questions are influenced--at least in part--by the effectiveness of predictive techniques and the hidden assumptions that govern their conclusions. (6)

    This Essay evaluates Virginia's risk assessment program as a means to probe our (dis)comfort with the use of predictive group statistics on individual criminals and to determine whether the statistical techniques adopted in Virginia are suitable for this important task. Part II gives the history of risk assessment in Virginia. Part III discusses the ethics of predictive sentencing of this sort. Part IV critiques the methodology of Virginia's approach and the errors that are introduced therein. Part V concludes the analysis.

  2. THE PATH TO RISK ASSESSMENT 1N VIRGINIA

    Virginia's experimentation with actuarial risk assessment in criminal justice has been marked by incremental change and paced implementation. The project began in earnest in 1994, when the General Assembly created the Virginia Criminal Sentencing Commission (VCSC or Commission) and instructed it to study the feasibility of placing twenty-five percent of nonviolent felons into alternative arrangements by determining who among the newly convicted posed the smallest risk to society. (7)

    This initiative was a direct consequence of Virginia's truth-in-sentencing reforms. After George Allen won the 1993 gubernatorial race largely by promising to eliminate parole and to increase penalties for violent crime, a commission recommended the widespread redrafting of Virginia's criminal statutes. (8) Unsurprisingly, with violent criminals serving as little as twenty-nine percent of their sentences for crimes as serious as first-degree murder, (9) there was pressure from both the public and Congress (10) to keep violent criminals behind bars for longer terms. Under Virginia's truth-in-sentencing program, violent convicts must serve at least eighty-five percent of their sentences, and in the first decade of the program, the average criminal served fully ninety percent. (11) Over that same decade, from 1994 to 2003, Virginia lowered its incidence of murder by twenty-eight percent. (12)

    While implementing truth-in-sentencing, Virginia was understandably concerned that increased prison sentences would lead to widespread prison overcrowding. In light of their instincts "[t]o reserve the most expensive resources for the most dangerous offenders, reformers underscored the importance of making the most efficient use of the state's remaining correctional resources to punish nonviolent offenders." (13) The newly-created VCSC's charge, then, was to find ways to keep unlikely recidivists out of the system.

    It bears mentioning, however, that this utilitarian-driven initiative conflicts with the underpinnings of truth-in-sentencing. The latter--also adopted by the federal government and several other states (14)--springs from a notion of "just deserts." (15) Violent sentences were increased and judicial discretion was largely curtailed under the theory that imprisonment is a "deserved punishment rather than ... a means for rehabilitation and treatment." (16) Conversely, the risk assessment pilot was grounded in a different, utilitarian theory of criminal law. It focused neither on punishing the guilty nor on rehabilitating the rehabilitatable. Rather, the question presented to the VCSC was the following: "Which nonviolent felony offenders are at a low risk of re-offending and can thus be safely placed in alternative sanction programs?" (17)--i.e., how can sentencing procedures be designed efficiently to protect the public-at-large?

    In developing its approach, Virginia confronted a number of initial decisions; namely, whether to conduct risk assessment or needs assessment and whether to rely upon clinical risk assessment or statistical risk assessment.

    In deciding between risk assessment and needs assessment, Virginia selected the former. The differences are meaningful. Risk assessment determines sentencing based only on the probability that a criminal will recidivate. (18) Although there is considerable disunity as to the definition of recidivism, (19) this approach focuses on the public and its instrumental interest in avoiding crime. Needs assessment, on the other hand, emphasizes an individual offender's need for services, so the potential effectiveness of treatment, counseling, or structured confinement can be incorporated into penal decisionmaking. (20) The VCSC, interpreting its mandate as limited to the "risk to public safety," chose to conduct only risk assessment. (21) Thus, the tool ultimately developed by the VCSC makes only a binary determination as to whether an offender should be sentenced to confinement in the penitentiary or whether some unspecified form of alternative sanction is objectively warranted. (22) The subjective determination of how best to accommodate eligible offenders' needs is made by judges and/or probation officers without any reference to statistics. (23)

    Despite the preference for clinical judgment in deciding between alternative sanctions, Virginia chose to implement statistical risk assessment to determine whether alternative sanctions would be recommended. Clinical models rely upon intuition and discretion often left in the hands of judges or medical professionals. (24) Conversely, statistical classification relies upon actuarial techniques to objectify the risks of future misconduct. (25) Inevitably, actuarial models cause individuals to suffer the consequences of the groups to which they belong. Nonetheless, various studies have found that actuarial methods can achieve better results than their clinical counterparts. (26) The Virginia legislature mandated a statistical approach (27) and the VCSC followed course.

    In pursuit of the legislated goal, the VCSC studied a random sample of roughly 1500 fraud, larceny and drug offenders who had each been incarcerated and released between July 1, 1991, and December 31, 1992. (28) The Commission tracked these subjects and tallied who among them was reconvicted for another felony within three years of initial release by mining data in a Pre/Post-Sentence Investigation Database. (29) Using multivariate logistic regression to study the correlation between personal characteristics and recidivism among those eligible for risk assessment, (30) the Commission developed a worksheet incorporating eleven factors and their expected contributions to recidivist tendencies.

    Figure 1 Factors Used To Predict Recidivism (31) Current Offense Information: 1. Offender gender 2. Offender age 3. Offender marital status 4. Offender employment status Current Offense Information: 5. Whether the offender acted alone when committing the crime 6. Whether there were additional offenses at conviction Prior Adult Criminal Record: 7. Whether the offender had been arrested or confined within the past 12 months 8. Offender's prior criminal record 9. Whether the offender had prior drug felony convictions 10. Whether the offender had been incarcerated as an adult Prior Juvenile Record: 11. Whether the offender had been incarcerated as a juvenile The Commission's study revealed that race was statistically significant but chose to omit this...

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