The Black Lives Matter movement and the recent focus in the media on how police interact with citizens of different races has helped engage Americans in an important conversation about how law enforcement works. Study afterstudy has found that black drivers are more likely to be stopped and arrested than whites.
But a closer look at some statistics shows that the problem is not necessarily an issue of racist cops, and that means fixing the criminal justice system isn’t just an issue of addressing racism in uniform.
Some racial disparities in treatment by authorities actually appear to be the result of state laws intended to crack down on offenses like drunk driving and scofflaws that have, instead, had the effect of ensnaring poor people in a revolving door of debt, courts, collections firms and police. My firm’s study of traffic stop data in Texas found evidence that the state wound up targeting low-income residents for heightened scrutiny and penalties. And because black and Latino Texans are disproportionately poor, these policies hit them harder — but because of the way Texas tracks such data, the unfair effects of the laws were hidden by what looked, on the surface, to be bad police work.
We looked at traffic stops in one Texas city whose stops did not fit any pattern of racial profiling. But when analyzing the resulting penalties from stops, at first glance, those sure looked like racism. (Under the terms of our agreement with the city, we can’t identify it here, but it’s a small city in the Dallas/Fort Worth metroplex.) In traffic stops during 2015, black women received citations for violations that levied fines, on average, of $204 more than white women, and $101 more per stop than Hispanic women. What’s more, minority drivers received slightly more violations per stop: Whites on average received 1.4 violations per stop, blacks 1.55 and Hispanics 1.6.
These numbers appear to indicate that the city’s police were systematically overcharging minorities. When we looked closer, though, a different picture emerged.
Our analysis showed that, by more than two to one, drivers were stopped for speeding. Once they were pulled over, the reasons drivers got additional citations varied by race. Where the most common secondary violation for white drivers was for “expired vehicle registration” (corrected for the cost of re-registration and a $10 fee), the most common second ticket for black drivers was for having a suspended driver license. “No driver license” was the most frequent second citation for Latino drivers — a common violation in a region with many undocumented immigrants
Suspended-license or no-license tickets are expensive. Why were so many blacks and Latinos driving on suspended or missing licenses?
Poverty.
The city in question is home to several large employers with low-wage but steady and respectable employment. More than 95 percent of the drivers stopped in this city last year lived outside its limits. Low-income workers in a region with no public transportation are more likely to have equipment violations on their older cars. When they get a $200 ticket for a broken headlamp, for example, they’re more likely to be unable to pay. (According toRice University, the 2009 Texas median household income for whites was $59,836, while for blacks it was $35,438, and for Hispanics $35,628.)
As in many states, unpaid citations here become arrest warrants. When they do, fines basically double, and the driver’s license is often suspended. Next time he’s stopped, the driver is cited for that violation and or driving with a suspended license. More than 1.3 million Texans have suspended licenses.
On top of the additional fines from violations like that, a 2003 Texas initiative to reduce drunk driving also levies heavy annual surcharges on anyone whose record includes certain offenses and suspensions.
This amounts to a poverty tax.
But the way Texas tracks stops obscures the broader unfair effects of the law on poor people, and makes it look, instead, like police are the problem. In our subject city, less than 7 percent of the population is black, but in 2015, 11 percent of the people pulled over there were.
That’s as far as Texas’ racial profiling laws want police chiefs to take their analysis. When chiefs track traffic stops, they must compare their driving population to the U.S. Census data for the city alone. That ignores the complexities of the driving public. What city’s drivers come only from within its limits?
In the city we studied, only about 5 percent of the people stopped there last year lived there. This is very common in smaller cities throughout the nation, especially those near larger ones, or those with universities, large hospitals and large employers. (Even in large cities, large numbers of drivers live elsewhere: 25 percent of those stopped by Philadelphia police in 2013 lived outside the city.) So we wanted to compare the traffic stop data to the population of the entire area where drivers came from. We looked at all the stops made within our subject city in 2015, including data on violations, race, gender, age and residence address. We grouped the home addresses of drivers stopped there by city of residence. Then we used census data on race and ethnicity to create a weighted racial-composition model for the region based on where most drivers stopped there live, and we compared that model against the race and ethnicity of the drivers who got pulled over.
The result showed that stops by this agency were anything but racist: White drivers were actually slightly overrepresented in the traffic stops compared to their share of the population in the city’s surrounding area, and black and Latino drivers slightly underrepresented. No group stood out in terms of non-compliant citations, arrests or searches.
Chiefs often do not conduct these kinds of analyses (which are required to recognize these patterns) because they spend their scarce resources complying with well-intentioned but ill-informed and often underfunded racial reporting requirements.
These issues are by no means limited to Texas, and they affect smaller departments disproportionately. Three-quarters of America’s 12,300 local police departments employed 24 or fewer officers; 48 percent employed fewer than 10 officers, and 5 percent employed a single officer. These challenges are faced by local police nationwide.
This leaves police — the most visible nexus between communities and the government — both unable to effectively lobby for the communities they actually serve, and dealing with potentially false but highly damaging accusations that cops select people to hassle based on their race.
If the problem were as simple as racist cops, the solution would be relatively easy: Identify them, train them and fire the ones who simply cannot function well in a diverse, multicultural society. But the real problem is finding the right data, and the right analytical techniques, to identify which officers are behaving poorly. Identifying “bad cops” is impossible when you don’t know how to identify good ones.
The fact is, most common police-data analysis techniques (and those of some reporters covering the law enforcement beat) are like the racial profiling techniques in Texas: well-intentioned but fatally flawed, making false equivalencies by conflating causes and correlations.
Changing the policing culture itself, and undoing laws that aggravate institutional racism, is much harder. That conversation must start with accurate data, analyzed fearlessly, honestly and well.