{"title":"Predictions of Dangerousness in Sentencing: Déjà Vu All Over Again","authors":"M. Tonry","doi":"10.1086/701895","DOIUrl":null,"url":null,"abstract":"Predictions of dangerousness are more often wrong than right, use information they shouldn’t, and disproportionately damage minority offenders. Forty years ago, two-thirds of people predicted to be violent were not. For every two “true positives,” there were four “false positives.” Contemporary technology is little better: at best, three false positives for every two true positives. The best-informed specialists say that accuracy topped out a decade ago; further improvement is unlikely. All prediction instruments use ethically unjustifiable information. Most include variables such as youth and gender that are as unjust as race or eye color would be. No one can justly be blamed for being blue-eyed, young, male, or dark-skinned. All prediction instruments incorporate socioeconomic status variables that cause black, other minority, and disadvantaged offenders to be treated more harshly than white and privileged offenders. All use criminal history variables that are inflated for black and other minority offenders by deliberate and implicit bias, racially disparate practices, profiling, and drug law enforcement that targets minority individuals and neighborhoods.","PeriodicalId":51456,"journal":{"name":"Crime and Justice-A Review of Research","volume":"48 1","pages":"439 - 482"},"PeriodicalIF":3.6000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1086/701895","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Crime and Justice-A Review of Research","FirstCategoryId":"90","ListUrlMain":"https://doi.org/10.1086/701895","RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CRIMINOLOGY & PENOLOGY","Score":null,"Total":0}
引用次数: 14
Abstract
Predictions of dangerousness are more often wrong than right, use information they shouldn’t, and disproportionately damage minority offenders. Forty years ago, two-thirds of people predicted to be violent were not. For every two “true positives,” there were four “false positives.” Contemporary technology is little better: at best, three false positives for every two true positives. The best-informed specialists say that accuracy topped out a decade ago; further improvement is unlikely. All prediction instruments use ethically unjustifiable information. Most include variables such as youth and gender that are as unjust as race or eye color would be. No one can justly be blamed for being blue-eyed, young, male, or dark-skinned. All prediction instruments incorporate socioeconomic status variables that cause black, other minority, and disadvantaged offenders to be treated more harshly than white and privileged offenders. All use criminal history variables that are inflated for black and other minority offenders by deliberate and implicit bias, racially disparate practices, profiling, and drug law enforcement that targets minority individuals and neighborhoods.
期刊介绍:
Crime and Justice: A Review of Research is a refereed series of volumes of commissioned essays on crime-related research subjects published by the University of Chicago Press. Since 1979 the Crime and Justice series has presented a review of the latest international research, providing expertise to enhance the work of sociologists, psychologists, criminal lawyers, justice scholars, and political scientists. The series explores a full range of issues concerning crime, its causes, and its cure.