Drivers, researchers and law enforcement departments have long tried to track traffic stop trends to see which groups of people are being pulled over and why.
Some point to racial profiling when numbers show a higher percentage of black or hispanic drivers are pulled over than white drivers within a community. Others cite faulty analysis, patrol patterns or enforcement technology that could skew numbers.
The truth could become clearer within the next four weeks, after a full report of traffic stop data from individual Connecticut law enforcement agencies is published. Shortly after, raw data collected from police is expected to be live online and available to the public.
The Connecticut Racial Profiling Prohibition Project (CTRP3) made an initial presentation June 26 to the Criminal Justice Policy Advisory Commission, revealing that the system for capturing criminal justice data isn’t just a concept anymore.
It exists, and it works, said Ken Barone, policy and research specialist at Central Connecticut State University.
Though trends show an overrepresentation of black and hispanic drivers in Connecticut who were stopped by law enforcement, Barone warned that the data hasn’t yet been placed into the context of each community. But the full report will do just that.
“We’re trying to understand why is it that whites, blacks, Hispanics [and other groups] are represented the way they are,” Barone said. “Are certain groups overrepresented in certain violations? Why are they overrepresented? Maybe there’s a disparity in the way we’re using technology across the state.”
The traffic stop data collection system is one of many projects that can be used to capture and report criminal justice information. Collected data goes into a system, and hopefully this can be replicated in other areas of criminal justice.
“It’s working, it’s working really well, and it wasn’t that difficult to put together,” Barone said.
Between October 2013 and April 2014, all 106 Connecticut law enforcement agencies with the power to pull someone over cooperated in collecting and reporting traffic stop information. Barone said about 95 agencies report data directly to the Criminal Justice Information System in real time.
This traffic stop information includes “characteristics of race, color, ethnicity, gender and age,” as the police officer perceives it, according to state law. It also includes the number of people stopped for violations, why they were stopped and the consequences of a violation.
The Alvin W. Penn Law — Connecticut’s anti-racial profiling law — also mandates that officers give drivers notice of how to file a complaint if they feel they were stopped on the basis of race, ethnicity, age, religion or other characteristics.
On average, 25 racial profiling complaints are investigated in Connecticut each year, according to the CTRP3 report.
Barone cautioned that while the currently available statewide data is interesting, more relevant data “drills down into each individual police department’s activity.” Benchmarks were developed to shed light on what influences trends in communities, which can inform Connecticut policy makers.
Benchmarks help analysts compare data to see if police activity shows bias, according to the report by CTRP3. Historically, traffic stop numbers have been compared to census data. But census data doesn’t perfectly represent the people who drive in a community, and people pulled over in a community don’t necessarily live there or contribute to its census data.
In the upcoming full report, data will be benchmarked by an estimated driving population, peer groups and state averages, according to the CTRP3 report. Additional criteria can be added if needed.
Managing the project is the Institute for Municipal and Regional Policy at Central Connecticut State University, governed by the Connecticut Racial Profiling Prohibition Advisory Board. Barone said they’ve been meeting for years to set the direction of this project.
Although all 106 agencies were compliant after October in reporting traffic stop information, in 2012, only 27 agencies collected and submitted traffic stop reports, which were supposed to be sent to the African American Affairs Commission at the time, according to the CTRP3 report.
Douglas Fuchs, police chief of the Redding Police Department, said the process is fairly automated now. Fuchs serves on the Connecticut Racial Profiling Prohibition Advisory Board, and he said that in the past, most law enforcement agencies were compliant, but there was no mechanism to collect or analyze the data.
“The largest key to this is an understanding of the actual driving population in a certain community,” Fuchs said. “One can’t only look at the population to determine who’s driving in that town or who works in that town. You need to drill down much further into the data to get a better understanding of who is driving in the community.”
This is the necessary context Barone mentioned. It’s the community-specific data that will be released in the full report later this month, complete with breakdowns of violation types, and it isn’t clear in the statewide data presented June 26 by CTRP3.
That data shows that black and hispanic drivers in Connecticut are stopped by law enforcement at a higher rate than their white and non-hispanic counterparts, using the broad method of comparing stop numbers to census data.
Connecticut police pulled over 303,863 drivers between Oct. 1, 2013, and April 30, 2014, according to the CTRP3 report.
About 14 percent of stopped drivers were black, with about an 8 percent black population — modified to reflect people 16 and older who have access to cars — in Connecticut. Almost 12 percent of drivers who were stopped were Hispanic, with an almost 10 percent Hispanic modified population.
White drivers made up 84.5 percent of the total drivers stopped by police, and white people are 84 percent of Connecticut’s population, modified.
However, though Asians comprise about 3.6 percent of the state’s population, modified, only about 1 percent of the stopped drivers were Asian.
“There’s so much when you look at the broad total state stop numbers,” Barone said. “Without understanding the context or the reason why those numbers are the way they are, I can’t answer what they should be.”
But after the full report is released and it becomes possible to “drill down” as suggested, someone might get close.