WHEN THE LEGISLATURE passed a law banning the use of handheld cell phones while driving, a major concern voiced by lawmakers was that it would be enforced disproportionately against Black and Hispanic drivers. Lawmakers required the state to conduct an annual analysis of traffic stops to identify racial disparities.
The first report resulted in mixed findings – and a shifting narrative on what exactly it concludes.
The Executive Office of Public Safety and Security released the 415-page study at 4 p.m. on February 7, leaving little time for journalists on a daily deadline to comb through it. The report used a Veil of Darkness analysis, which, a press release from the agency said, “found no support for patterns of racial disparity in traffic stops.”
The analysis compared traffic stops during the day and night, assuming police can more easily identify race during daylight. Many of the first news stories on the report leaned heavily on the executive summary and press release.
“Study finds no evidence of racial disparity in traffic stops by police in Massachusetts,” the Associated Press wrote. “Massachusetts data analysis finds no support for patterns of racial disparity in traffic stops,” wrote the Fall River Reporter.
But Arnie Stewart, deputy chief counsel at the Committee for Public Counsel Services, said at a public hearing Wednesday the stores were wrong. “Nothing could be further from the truth,” he said.
As advocates digested the report, many say the report’s findings are complicated and actually demonstrate significant disparities.
WCVB wrote explicitly in its headline: “More evidence of racial bias seen in Massachusetts police stops than state news release suggests.” The Boston Globe followed up its initial story – “Report finds no support for patterns of racial disparity on who is pulled over, but drivers of color were more likely to be searched, cited” – with a subsequent story headlined “For some, report on Mass. traffic stops shows stubborn racial biases persist in policing.”
At Wednesday’s hearing, the third one held by the Executive Office of Public Safety and Security, attorneys and advocates laid out some of the problems identified by the report, including data limitations that researchers acknowledged.
“Despite the claim stated in the report that there was no support for patterns of racial disparities in traffic stops, a shallow dive into the data highlights the inequitable impacts of these stops,” said Seleeke Flingai, senior research associate at the Vera Institute of Justice, a left-leaning criminal justice policy group.
Stewart said the data show that Black and Hispanic drivers were more likely to receive a criminal citation, get arrested, and be subjected to a search after a traffic stop than White drivers. Black and Hispanic drivers were least likely to get a written warning. “This is racial disparity,” Stewart said. “Race is a factor in Massachusetts traffic stops because racism is alive and thriving.”
Stewart said one problem with the study’s methodology is caused by the legislation mandating the study, which required that only data on stops resulting in a written citation would be collected. Stewart, who is Black, cited her own experience driving with a colleague from Jamaica Plain to Brighton at midnight. Three times, she said, a police officer started following her. “My White colleague said to me, ‘I’ve never seen anything like this, you’re like a police magnet,’” Stewart said. “I said to her ‘this is my life, this is not unusual.’ What was unusual was that I wasn’t stopped that night.”
Joshua Raisler Cohn, an attorney with the Committee for Public Counsel Services, questioned whether Veil of Darkness is an accurate method of assessing racial bias, since an officer can identify a driver’s race in a well-lit area at night, and the police can run a license plate and learn a driver’s race before pulling them over.
Francis Olive, an assistant professor at Worcester State University who worked on the report, said Veil of Darkness is the “most rigorous analysis” available to examine racial disparities. But he acknowledged that there are data limitations: the police are not collecting data on verbal warnings; the data does not indicate the main reason for a stop if there are multiple infractions; it does not say whether searches found contraband; and it doesn’t distinguish between a stop made with a warrant and a discretionary stop.
Olive said if disparities are detected, researchers must dig deeper to understand why. “Disparity does not equal discrimination or profiling,” Olive said.