Race-Norming and Statistical Discrimination: Beyond the NFL

Sonja B. Starr (University of Chicago), Race-Norming and Statistical Discrimination: Beyond the NFL, SSRN (2022):

This Article uses the recent NFL “race-norming” scandal—in which Black players with concussion claims were scored differently on cognitive impairment tests, based on the assumption that they were less intelligent at baseline—as an entry point to a broad-ranging analysis of inconsistencies in the law’s treatment of statistical discrimination. The Supreme Court has emphatically and repeatedly rejected efforts to justify otherwise-illegal discrimination against individuals by resort to statistical generalizations about groups. This doctrine makes practices like the NFL’s not just repugnant, but illegal—yet such practices are pervasive and persistent, in high-stakes settings far beyond the NFL. Similar race-norming in diagnostic algorithms is ubiquitous in medicine, for example, but has avoided legal scrutiny. Moreover, the justice system itself has embraced numerous similar practices, including demographic norming of intellectual-capacity assessments for defendants facing the death penalty, explicit class-based discrimination in criminal justice risk assessments, and the use of race- and sex-specific actuarial data to calculate tort damages. This Article examines these practices, the law governing them, and the reasons for these disconnects between law and practice.