Situating the Prediction Problem Within Collateral Consequences

• Author: Mike Vuolo
• Date: 01 August 2017
• Published date: 01 August 2017
• DOI: http://doi.org/10.1111/1745-9133.12327

EDITORIAL INTRODUCTION

REDEEMED COMPARED TO WHOM?

Situating the Prediction Problem Within

Collateral Consequences

Communicating Risk to Employers

Mike Vuolo

The Ohio State University

In bridging criminological theory with public policy,the fundamental scientific endeav-

ors of prediction and classification maintain a central place. Yet in predicting future

criminal behavior, the stakes for individuals and organizations in the possibility arising

from both false positives and false negatives are consequential. D. Gottfredson (1987) noted

this “prediction problem” within the criminal justice system, which is tasked with decisions

such as bail amounts, sentencing to probation versus incapacitation, and granting parole. As

the focus on collateral consequences has expanded, criminologists have come to understand

that criminal justice system actors are not the only ones making consequential decisions for

individuals’ lives based on their propensity for future criminal behavior. Rather, the pre-

diction problem also arises in other arenas, perhaps most consequentially in employment.

Within this context, the importance of the article by Samuel DeWitt, Shawn Bushway,

Garima Siwach, and Megan Kurlychek (2017, this issue) becomes clear. How do we classify

individuals as at risk of criminal behavior so that we can make appropriate comparisons,

and how do we predict it? Indeed, this article and the policy essays by Kiminori Nakamura

(2017, this issue) and Michael Gottfredson (2017, this issue) harken back to some of the

key issues outlined within the criminal justice system by D. Gottfredson (1987).

As the title of DeWitt et al.’s (2017) article implies, the key to classification in em-

ployment decisions is what two groups to compare. As is emphasized in the policy essays

(M. Gottfredson, 2017; Nakamura, 2017), DeWitt et al. take a clever approach to clas-

sification. Instead of comparing offenders with nonoffenders or the general population,

DeWitt et al. compare the offending risk with those hired without criminal records within

the same employee pool. In prior studies, researchers did not consider that employers

Direct correspondence to Mike Vuolo, Department of Sociology, The Ohio State University, 238 Townshend

Hall, 1885 Neil Avenue Mall, Columbus, OH 43210 (e-mail: vuolo.2@osu.edu).

DOI:10.1111/1745-9133.12327 C2017 American Society of Criminology 959

Criminology & Public Policy rVolume 16 rIssue 3