A new study titled, “A large-scale analysis of racial disparities in police stops across the United States,” found that in a dataset of nearly 100 million traffic stops across the United States, black drivers were about 20 percent more likely to be stopped than white drivers relative to their share of the residential population.
The study, the largest of its kind, was undertaken by the Stanford Open Policing Project, which aims to collect, standardize, release, and analyze hundreds of millions of traffic stop records throughout the country to help researchers, journalists, and policymakers investigate and improve interactions between the police and the public.
The study also measured the disparity in stop rates before and after sunset. It found that black drivers made up a smaller share of those stopped at night, when it’s more difficult to discern the race of a driver, which suggests that racial bias may influence stop decisions. For example, in Texas, about 25 percent of drivers stopped right before sunset were black, compared to about 20 percent just after dusk. The analysis found the same basic pattern across all the stops in aggregate. Overall, the data showed about a 5-10 percent drop in the share of drivers stopped at night who are black.
“Our team contacted over 100 city police departments and processed and released over 20 million traffic stop records, in addition to the more than 150 million state-level traffic stop records that were also simultaneously released,” Shroff said. “It was a challenging task, but we hope the public release of this extensive dataset and analysis will provide new insight into the nature of law enforcement interactions with the public.”
The study also found that once stopped, black drivers were searched about 1.5 to 2 times as often as white drivers, yet officers found drugs, guns or other illegal contraband on black drivers less often than on white drivers, pointing to a double standard in search decisions.
“Looking at millions of traffic stops across dozens of jurisdictions, we found evidence of widespread racial bias in who is stopped and searched by the police,” said Sharad Goel, an assistant professor in the School of Engineering at Stanford and the executive director of the Stanford Computational Policy Lab.
In recent years, incidents related to police stops have captured public attention over possible bias in policing.
“This data helps show the evidence behind the anecdote,” said Cheryl Phillips, the Lorry I. Lokey Visiting Professorin Professional Journalism at Stanford and co-founder of the project.
In some cases, it is clear that police strategies may be geared toward reducing crime but could have unintended consequences of increasing disparate treatment of black and Hispanic drivers. For example, in an in-depth analysis of traffic stops in Nashville, the team found a high incidence of stops for equipment violations — such as broken tail-lights — which did not appear to reduce crime rates but disproportionately impacted minority drivers.