Lessons Learned: Collecting Data in Officer Traffic Stops, <i>Police Chief</i> Magazine

Lessons Learned: Collecting Data in Officer Traffic Stops

From the July 2001 Police Chief Magazine

By Colonel Jerry A. Oliver, Chief of Police, and Alicia R. Zatcoff, Project Manager, Richmond, Virginia, Police Department

"Another day, another ambush." If that phrase accurately depicts your thoughts as you walk into a community meeting to discuss the issue of racial profiling, then you are not alone.

While police chiefs across the country continue to struggle with this cantankerous subject, the Richmond, Virginia, Police Department has chosen to look at it as an opportunity. It is an opportunity to address what we believe is the underlying problem: the minority community's lack of trust in the government and its most visible arm, the police.

Recently enacted legislative mandates require police departments in a number of jurisdictions to collect statistics on the race of motorists stopped by officers. The Richmond Police Department voluntarily collects these statistics. Our decision to voluntarily compile information is not unique, but I believe we have learned some valuable lessons from which other law enforcement agencies in the beginning stages of their collection efforts may benefit.

In order to address the perception of racial profiling among our citizens, we felt it was necessary to truly engage the community by including citizens in the development of the program. We created a traffic stops task force and invited more than 20 citizens to participate along with officers and other employees of the police department. The president of the local chapter of the NAACP and the leader of the local Muslim temple as well as local business owners, ministers, and community activists served on the task force.

The task force represented the diversity of our community. Initially, much disagreement and misunderstanding existed. However, through a series of discussions, task force members gained awareness and respect for each other's thoughts and opinions. Working through the disharmony and rancor within the group is what strengthened the credibility of the task force's final proposal for the collection of statistics.

Additionally, the recommendations were useful because they incorporated concerns of both the community and the police department.

Armed with the task force recommendations, we turned to developing and implementing the protocol to collect data. We ran a 10-week test from January 17, 2000, through March 31, 2000, in an effort to determine whether white officers treat minority drivers differently within the context of a traffic stop.

Method

Each police officer was required to complete an electronic survey form at the completion of each traffic stop (a complete listing of the survey variables is available from the Richmond Police Department, (804) 780-6700, upon request). For the data collection, we used the officer's perceptions of the driver's race. While we knew that these would not be completely accurate, we felt that the officer's perception of the driver's race would be the most salient predictor of racial profiling, if it existed.

In addition, members of the citizen task force believed that requiring the officer to ask the motorist to identify his or her race had the potential to be inflammatory in the context of a traffic stop. Moreover, to ensure overall consistency, each officer would be required to ask each motorist, regardless of his or her apparent race. Again, it was thought that this practice would be offensive to many motorists, and it was determined that the officer's perception of driver race would be the relevant variable in any potential racial profiling.

Results

During the sampling period, officers collected data from 4,376 stops. Official records identified 6,520 stops, which yielded a response rate of 67 percent. Because the survey was anonymous, it was not possible to determine demographic characteristics of the individual officers involved in the study; but African American and white officers made 18 and 80 percent of the stops, respectively.

For reasons cited above, actual driver race was not available. However, the apparent driver race was 64 percent African American and 32 percent white. Additional review of the data suggested no difference between African American and white officers in the rate of traffic stops of African American drivers. African American motorists made up 64 percent of the total stops involving both African American and white officers. Similarly, there were no notable differences between African American and white officers in the rate of traffic stops for white motorists. White drivers made up 31 percent of the total stops involving African American officers and 32 percent of the stops involving white officers.

Discussion

While the results are encouraging, several procedural flaws in our data collection significantly limited our ability to interpret the results and determine whether white officers treat minority drivers differently within the context of a traffic stop. Therefore, the flaws outlined below will need to be addressed before we can determine whether all motorists in our community are treated fairly and equally.

First, we made the decision to blind the data with respect to individual officers in an effort to ensure their anonymity. We expected that this would encourage the officers to be honest in their reporting. Unfortunately, the reporting compliance was relatively low (67 percent). Moreover, our inability to link a particular officer to a series of stops precluded our ability to determine the actual frequency and nature of stops per officer. For example, it was impossible to determine whether 100 stops involving white officers and African American motorists reflected 100 officers making one stop, ten officers making ten stops, or one white officer stopping 100 African American motorists. Similarly, it was impossible to determine what percentage of an officer's total workload these stops represented.

The second flaw in the test phase protocol was the low response rate—only 67 percent. This issue was particularly troubling, given that completion of the traffic survey was mandatory. Again, while the results from the present study do not support racial bias, it is possible that officers concerned about their practices may have elected not to participate in the study given the sensitivity associated with racial profiling. This may have introduced positive bias into our data.

Unfortunately, an analysis of nonresponders was not feasible because it was not possible to directly link individual officers to specific traffic stops. It was not clear whether 33 percent of the officers never completed the survey, or whether all of the officers did not complete a survey for 33 percent of their stops, because it was not possible to specifically identify individual officers. The truth probably lies somewhere in between, but the low response rate is troubling and limits our ability to analyze and interpret the data.

In summary, despite these methodological flaws, the overall effort to collect data was a positive experience. First, we were able to convey to the community that we were very concerned about this issue. By partnering with local citizens, we were able to frankly discuss difficult subjects in an open and constructive forum. The citizen input was invaluable, particularly regarding the decision how to conduct the survey in the least offensive manner, given the sensitive issues involved. Although there were flaws in the data that significantly limited our ability to determine whether white officers treat minority motorists differently, we believe that with the ongoing support of our citizens these issues will be easily addressed.