High-frequency location data show that race affects citations and fines for speeding

• 成果类型: Article
• 署名作者: Aggarwal, Pradhi; Brandon, Alec; Goldszmidt, Ariel; Holz, Justin; List, John A.; Muir, Ian; Sun, Gregory; Yu, Thomas
• 署名单位: Massachusetts Institute of Technology (MIT); Johns Hopkins University; University of Chicago; University of Michigan System; University of Michigan; Washington University (WUSTL); Yale University
• 刊物名称: SCIENCE
• ISSN/ISSBN: 0036-10119
• DOI: 10.1126/science.adp5357
• 发表日期: 2025-03-28
• 页码: 1397-1401
• 关键词: motor-vehicle searches; racial bias; tickets; machine

摘要

Prior research on racial profiling has found that in encounters with law enforcement, minorities are punished more severely than white civilians. Less is known about the causes of these encounters and their implications for our understanding of racial profiling. Using high-frequency location data of rideshare drivers in Florida (N = 222,838 individuals), we estimate the effect of driver race on citations and fines for speeding using 19.3 million location pings. Compared with a white driver traveling the same speed, we find that racial or ethnic minority drivers are 24 to 33% more likely to be cited for speeding and pay 23 to 34% more money in fines. We find no evidence that accident and reoffense rates explain these estimates, which suggests that an animus against minorities underlies our results.