As I mentioned yesterday, I take exception with the ACLU's assertion that racial disparity in traffic stop data indicates"alarmingly high" rates of racial profiling. Disparity and profiling are not the same. While I think the disparity should cause (and has caused) us to step back and take a good look at what's going on, to conclude that racial profiling is causing the disparity without further examination is a logical leap.
Profiling, the act of targeting people of color due to their race, assumes that police officers and agencies, either intentionally or subconsciously, are acting upon racial prejudice and bias. Disparity however, can occur for a variety of reasons. For example, the Crime Commission compares traffic stops to population demographics. But what if census data doesn't reflect who's actually on the road, or what their likelihood is of committing a traffic infraction? A better denominator than population might be the data on licensed drivers, or maybe the age profile of drivers (since we know age is related to traffic violations), or an actual roadside count of motorists.
After lots of thinking about this over the past 12 years, and lots of exploration in our data, I think the best denominator is involvement in traffic collisions. One's likelihood of being stopped, all other things being equal, ought to approximate the race of the 12,915 drivers who were involved in traffic crashes in Lincoln last year. Crash data would automatically account for racial differences in driving behavior, age profile, driving frequency, and mileage. What it would not account for, however, is where the police are actually patrolling, and the racial makeup of the people driving in these areas.
Some racial disparity in traffic stops may be the result of the common police practice of deploying officers into areas where crime and disorder problems are most prominent. We work very hard on this in Lincoln, as does Omaha, and we've gotten much better at it with sophisticated crime analysis and GIS. There are far more officers per square mile in the areas with high crime and disorder, and these also tend to be lower income and considerably more diverse.
This screen shot is from HunchLab 2.0, one of the analytical software products we use to forecast hotspots of crime in the next few hours. The colored blocks are individual cells or groups of cells. Each is a 200 meter square area where the risk of crime is elevated, and the colors denote the dominant crime type. The cluster in the core of the city south of downtown and along 27th Street is persistent, and this is the area of Lincoln where you will find the highest concentration of police officers. It is also among the most racially diverse areas in Lincoln.
As a result of the deployment pattern, the likelihood of police stops in these areas is greater in the areas where there is also a greater percentage of minorities than in the general population. You can question the deployment strategy, but if some of the disparity in stops is emerging from this cause, rather than from police bias, that portion is not racial profiling. If you want to impact this portion of disparity, all the sensitivity and cultural awareness training on earth will fail. Rather, you need to convince the police to deploy differently. We could have a healthy discussion about that, but I think people living and working in Lincoln neighborhoods that are most impacted by crime and disorder generally want more police presence and activity, not less.
The type of activity, however, is also relevant. I believe that problem-solving, prevention, and early intervention, ought to be an important part of the mix, and are less likely to be perceived as racially-motivated than some other tactics, such as intensive use of stop-and-frisk. When the community sees the police working collaboaratively with the neighborhood stakeholders, it is less likely to view such things as arrests, traffic stops, and hot spot patrols as bias-based, and more likely to view these are legitimate efforts to reduce crime and disorder.
Links to the series: