RESEARCH TRIANGLE PARK, NC — Black male drivers were disproportionately pulled over in traffic stops conducted by the Durham Police Department from 2010 through 2015, according to a new study by RTI International.
Researchers found that when traffic stops involved male drivers, the odds of the driver being black were 20 percent higher during times of daylight, when the race of the driver is more clearly identifiable, than during times when it was dark outside.
No evidence of racial bias was found among female drivers.
RTI researchers were also able to identify differences in racial disproportionality by police unit. They found the most disproportionality in stops conducted by the High Enforcement Abatement Team, a unit focused on drug, vice and gang violence. The results showed no evidence of disproportionality among the stops conducted by the department's dedicated Traffic Unit.
The results also suggest that racial disproportionality declined over the six-year study analysis period. Black males were most over-represented from 2010 through 2013. By 2014, black males were stopped at nearly the same rate when there was daylight and when it was dark. This suggests that disproportionality in traffic stops was declining during 2014 and 2015.
"Although there is evidence of racial disproportionality, the evidence suggests that this disproportionality has been declining in recent years," said Travis Taniguchi, PhD, a research criminologist at RTI. "This improvement may have been the result of changes in Durham Police Department training or policies."
Researchers analyzed data from 151,700 traffic stops conducted by the Durham Police Department from January 2010 to October 2015. Traffic stop data was provided to RTI by the Durham Police Department in an effort to promote transparency and better understand their operations.
"This is a study that the Durham Police Department requested to determine the possibility of bias being a factor in our traffic stops and examine if the changes we've put in place sufficiently addressed those concerns," said Interim Police Chief Larry Smith. "It's essential that we get an objective view of our operations and in turn be willing to not only accept the findings, but continue to work toward putting the necessary tools in place to correct the issues this analysis revealed—and ensure that bias of any kind is never a part of police operations."
To test for racial bias in traffic stops conducted by the Durham Police Department, researchers used the "veil of darkness" approach, which is based on the assumption that officers are unable to observe the race of a driver when it is dark outside. By using this method, researchers explored racial disproportionality by comparing the race of drivers stopped during daylight to the race of those stopped during darkness. The study examined traffic stops during the intertwilight period roughly between 5:30 p.m. and 9 p.m.; during which it is light at some times of the year but dark during other times.
Researchers also used the veil of darkness approach to study state-sourced traffic stop data from Raleigh, Fayetteville and Greensboro. No evidence of racial bias was found in these cities.
"Raleigh, Fayetteville and Greensboro have all had long-term media attention on the racial composition of drivers stopped by those departments," Taniguchi said. "Our analyses of these cities failed to identify evidence of racial bias. Media attention and benchmarks against census population appear insufficient to reliably identify disproportionate minority contact in traffic stops."
RTI self-funded this research as a service to the community and to contribute to the growing scientific research on this topic.
As part of this research, RTI is also developing a free online tool that will allow law enforcement agencies to conduct the veil of darkness analysis on their own traffic stop data. This tool will automate the time consuming process involved with conducting the veil of darkness analysis. The tool will be made available in a few weeks, and will be provided free of charge to law enforcement agencies and parties interested in taking a closer look at the racial composition of traffic stop data.
"Many law enforcement agencies are collecting these kinds of data, but often don't have the time or expertise to analyze them in a scientifically rigorous manner," Taniguchi said. "This tool will assist agencies in understanding whether or not there is evidence of racial bias in their traffic stops."
