Racial bias not a significant factor in nearly 160,000 traffic stops by Suffolk cops, study finds

Racial bias did not play a significant factor in traffic stops by Suffolk police officers, according to a new report posted on the department’s website earlier this week that examined nearly 160,000 stops in 2023.

Stonewall Analytics said the methodology of the report, "2023 Traffic Stop Data Analysis," included the "Veil of Darkness" test, which assumes that officers are less able to discern a driver’s race and ethnicity in the dark, and compares countywide traffic stops made during daylight and nighttime hours.

"The results showed no statistically significant relationship between daylight stops and the likelihood of stopping minority drivers, as compared to white drivers," the report said.

The "2023 Traffic Stop Data Analysis" report noted that 19% of the motorists stopped were Black, even though they represented 9.6% of the county’s population that year. Suffolk’s Hispanics — making up 23.1% of Suffolk’s 2023 population — represented 27.9% of those stopped. Non-Hispanic whites made up 62.7% of the county’s population and 45.4% of traffic stops.

The Suffolk County Police Department was required to hire a third party to analyze traffic stop data as part of its 2023 settlement with LatinoJustice, a Manhattan civil rights organization that accused the agency of widespread discrimination against Latinos in a 2015 lawsuit.

The 2023 settlement with LatinoJustice called for the county to codify elements of the police reform plan adopted by lawmakers in 2021 for at least three years, even if a new police commissioner or county executive wishes to repeal them.

In addition to public disclosure of traffic stop data, the initiatives in the settlement also included the creation of precinct advisory boards and equipping officers with body cameras.

The agreement also called for Suffolk to pay $75,000 to 20 plaintiffs named in the lawsuit. The suit was originally brought on behalf of Latino residents of Suffolk who were victims of race-based stops, detentions and other harassment, according to the 2015 complaint.

Suffolk Police Commissioner Kevin Catalina said the department is pleased with the outcome of the report and committed to bias-free policing. 

"Roadway safety is a paramount concern for all residents of Suffolk County and as we implement new and enhanced initiatives to reduce crashes and ensure public safety, we will maintain ongoing scrutiny of our stop and enforcement data to ensure equitable policing practices," Catalina said.

But community advocates were skeptical of the findings, saying the conclusions reached by the Idaho-based data science company are based on inadequate research and whitewash discriminatory policing practices.

LatinoJustice deputy general counsel Jose Perez said the report was based on incomplete data and does not fulfill the requirements of the lawsuit settlement. 

"While it would be gratifying to believe that the department has made a 180-degree turn in the past two years, presenting data on stops without also parsing out the outcomes of those stops is far from conclusive and skirts the parts of the agreement with the SCPD to gather adequate data so the public can monitor their actions," Perez said.

Terryl Dozier, of LI United, a community group pushing for police reform, said the report’s conclusions are "disingenuous."

"SCPD continually fails to adequately explain why Black and Hispanic drivers are stopped disproportionately to their population relative to white drivers," Dozier, also a member of Suffolk's Second Precinct Level Advisory Board, said in an interview.

Stonewall Analytics did not respond to requests for comment. The company's website said it provides data analysis and survey research, and that its clients have included the U.S. Department of Justice, the Pennsylvania Department of Transportation, the Alaska Department of Health and Social Services, and Clemson University.

The report also concluded that Suffolk police were more likely to find illegal drugs, weapons and other contraband during traffic stops with searches of white drivers than minority motorists, although the "difference was not statistically significant, suggesting that variations in search outcomes may be influenced by other factors rather than bias in policing practices."

The $35,750 study does not consider traffic stop data from other years. Suffolk police have shared traffic stop data with the public since 2018, including a breakdown of stops by race and ethnicity, on the "transparency hub" portion of the department's website.

The LatinoJustice lawsuit argued that police continued to engage in discriminatory behavior even after the U.S. Justice Department launched an investigation into the department in the wake of a fatal attack on Marcelo Lucero, an immigrant from Ecuador, in 2008 by a group of teens. Suffolk police entered an agreement to reform its policies with the Department of Justice in 2014.

"The evidence we gathered in our case of years of targeted abuses by SCPD officers, with knowledge and support from their superiors, was so wide-ranging that the federal judge who certified the case as a class action issued a 38-page report that recognized the ‘voluminous record’ of department policy failures that officers and their superiors had carried out," Perez said in an email.

Another advocate criticized the study methodology. The Veil of Darkness theory is flawed, said Peggy Fort, of United for Justice in Policing Long Island, because many of Suffolk County’s roads are well-lit at night.

"Apart from street lighting, given Suffolk County’s segregated residential housing patterns and vehicle models and ages, it is utterly fantastic to suggest that an officer who is familiar with his or her patrol sector cannot reasonably discern the race and ethnicity of vehicle occupants once the sun has set," she said in an email.

Frank R. Baumgartner, a University of North Carolina political science professor who has researched traffic stops, said the Veil of Darkness test is an inadequate measure because it does not examine bias in departments’ policies. Officers may pull over more Black and Hispanic motorists per population, he said, because of more aggressive policing in those communities, said Baumgartner, the author of "Suspect Citizens: What 20 Million Traffic Stops Tell Us About Policing and Race."

"If you deploy more officers in Black and brown communities after dusk," Dozier agreed, "you are going to pull over more Black and brown drivers."

LatinoJustice has commissioned an expert to analyze traffic stop data made public by Suffolk police, Perez said, and expects to release its own report next month.

 "We will continue to monitor data collection and transparency, as well as practices by the SCPD, to ensure that Latino residents and motorists in the county are not subjected to further bias-based policing practices," he vowed.

A Newsday investigation in 2020 found that the Suffolk County Police Department subjected Black and Hispanic drivers to tougher enforcement actions than white motorists over the past two years, stopping and then searching the minority drivers and their vehicles at higher rates than experienced by whites.

Officers pulled over Black drivers almost four times more often than white drivers, and Hispanic drivers twice as often, when matched against the size of the driving age population of each group in the area patrolled by the Suffolk Police Department.

More tellingly, after stopping drivers, police searched Black drivers over three times more frequently than whites, and Hispanics 1.7 times more frequently, Newsday’s analysis revealed.

At the same time, Suffolk police found contraband, such as an illegal weapon or drugs, when searching Black and Hispanic drivers less frequently than when they searched white motorists.

Traffic stops for offenses such as speeding, failure to signal and broken taillights are the most common — and familiar — enforcement actions taken by police. Because officers have discretion to choose which drivers to pull over and, critically, which to search, stops can also reveal evidence of whether a department applies the laws equally to members of different races or ethnicities.