Evidence-Based Sentencing and the Scientific Rationalization of Discrimination

This Article critiques, on legal and empirical grounds, the growing trend of basing criminal sentences on actuarial recidivism risk prediction instruments that include demographic and socioeconomic variables. largue that this practice violates the Equal Protection Clause and is bad policy: an explic...

Full description

Saved in:
Bibliographic Details
Published in:Stanford law review 2014-04, Vol.66 (4), p.803-872
Main Author: Starr, Sonja B.
Format: Article
Language:English
Subjects:
Age
Attitudes
CRIMINAL JUSTICE
Criminal sentences
Criminal sentencing
Criminals
Decision making
Defendants
DISCRIMINATION
Endorsements
Equal protection
Equal rights
Equality before the law
Evaluation
EVIDENCE
Evidence, Criminal
Gender
Government regulation
Imprisonment
Incarceration
Judges
Judges & magistrates
JUDICIARY
Laws, regulations and rules
Methods
Neighborhoods
Rationalization (Psychology)
Recidivism
Recidivism prediction
REPEAT OFFENDERS
Risk analysis
Risk assessment
Sentenced offenders
Sentences (Criminal procedure)
SENTENCING
Social aspects
Social economics
Socioeconomic factors
Socioeconomics
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This Article critiques, on legal and empirical grounds, the growing trend of basing criminal sentences on actuarial recidivism risk prediction instruments that include demographic and socioeconomic variables. largue that this practice violates the Equal Protection Clause and is bad policy: an explicit embrace of otherwise-condemned discrimination, sanitized by scientific language. To demonstrate that this practice raises serious constitutional concerns, I comprehensively review the relevant case law, much of which has been ignored by existing literature. To demonstrate that the policy is not justified by countervailing state interests, I review the empirical evidence underlying the instruments. I show that they provide wildly imprecise individual risk predictions, that there is no compelling evidence that they outperform judges' informal predictions, that less discriminatory alternatives would likely perform as well, and that the instruments do not even address the right question: the effect of a given sentencing decision on recidivism risk. Finally, I also present new empirical evidence, based on a randomized experiment using fictional cases, suggesting that these instruments should not be expected merely to substitute actuarial predictions for less scientific risk assessments but instead to increase the weight given to recidivism risk versus other sentencing considerations.
ISSN:0038-9765
1939-8581