By  Griffin Sims Edwards and Stephen Rushin

This Article examines the effect of state laws restricting the use of police quotas. Police quotas describe the establishment of a predetermined number of traffic stops, citations, or arrests that officers must make within a particular time period. Some police supervisors have historically used quotas to ensure adequate productivity by officers. However, critics argue that quotas incentivize officers to engage in unnecessary, and in some cases, unconstitutional, coercive behavior. Numerous states across the country have enacted laws banning or limiting the use of police quotas.

This Article analyzes a dataset of traffic and pedestrian stops from eleven law enforcement agencies with varied laws on police quotas over time. It finds minimal evidence that laws limiting police quotas reduce coercive behavior by police. If anything, agencies may engage in slightly more coercive behavior after the introduction of these laws. However, we find evidence that restrictions on the use of police quotas may improve the quality of traffic stops and vehicle searches.

We offer several hypotheses to explain these results. First, the narrow focus of quota laws may limit their effectiveness. Second, the managerial tactics that replace police quotas may incentivize officers to engage in similar amounts of coercive behavior. And third, the relatively weak enforcement mechanisms in state quota bans may reduce their deterrent effect.

We conclude by discussing the implications of these findings for the literature on police regulation. We also offer recommendations for reforming police quota laws.

109 Iowa Law Review 2127 (2024), 

By The Virginia Department of Criminal Justice Services

The Community Policing Act of 2020 (HB 1250; “the Act") mandated that the Virginia State Police (VSP) and other state and local law enforcement agencies, including police departments (PDs) and sheriff’s offices (SOs), begin collecting and reporting data on traffic stops as of July 1, 2020. State law enforcement agencies, PDs, and SOs are required to collect data on the race, ethnicity, and other characteristics of the drivers stopped, and on other circumstances of the stop such as the reason for the stop, whether any individuals or vehicles were searched, and the outcome of the stop (arrest, citation, warning, etc.). All reporting agencies are to submit this data to VSP, who maintain the data in the Community Policing Database.

The Act also mandated that the Virginia Department of Criminal Justice Services (DCJS) periodically obtain data from the Community Policing Database and produce an annual report “for the purposes of analyzing the data to determine the existence and prevalence of the practice of bias-based profiling and the prevalence of complaints alleging the use of excessive force." Such reports shall be produced and published by July 1 of each year.

This is the third of these reports from DCJS. It contains a review of how the data was collected and analyzed as well as preliminary findings of data from 650,387 traffic stops reported in Virginia during the nine-month period between July 1, 2022, and March 31, 2023. This report also presents the findings from analyses of statewide data; aggregated data from the seven VSP Divisions; and data from each individual law enforcement agency that reported sufficient data to the Community Policing Database.

The information presented in this report is preliminary and should be interpreted with caution. Although this analysis identified disparities in traffic stop rates related to race/ethnicity, it does not allow us to determine or measure specific reasons for these disparities. Most importantly for this study, this analysis does not allow us to determine the extent to which these disparities may or may not be due to bias-based profiling or to other factors that can vary depending on race or ethnicity. These other factors include differences in locations where police focus their patrol activities, differences in underlying regional populations, differences in driving patterns among individuals, and the lack of a scientifically established baseline for determining the number of drivers in each racial/ethnic group who are on the road and subject to being stopped while driving.

The analysis of racial disparity is a complex field with a vast array of potential contributing factors. Many data elements could play influential roles in racial/ethnic patterns of traffic enforcement but are unavailable to DCJS. Factors like the race of the officer performing the stop, agency policies and community priorities driving enforcement patterns, police report narratives outlining legal justifications for stop, search, and arrest can all inform stop patterns but are not within the current purview of available Community Policing Act data. Additionally, the data presented in this report cannot reflect any stop trends from agencies which did not provide data or records that were excluded for completeness issues. As such, while the report presents stop, search, and arrest disparities based on the available data, they should not be construed as complete and final proof of disparity OR any explanation of contributing factors which drive genuine disparities which may exist.

This report does not tabulate the many positive actions that can occur for a traffic stop such as seizures of guns, confiscation of drugs, and ensuring valid and current drivers’ licenses. The Community Policing Act imposes narrow requirements for data collection and analysis, and any benefits of traffic or pedestrian stops are not within the scope of the law.

While DCJS and VSP have introduced process improvements based on lessons learned in past reporting, the Community Policing Act is still in the early stages of implementation. More and better data, as noted in the recommendations, is needed to make the observations in this report more than directional, and the costs of such data gathering need further evaluation. As the report notes, many PDs and SOs − especially smaller agencies with limited resources − continue to face challenges establishing the data collection and reporting required under the Act. The majority of local law enforcement agencies (LEAs) in Virginia (255, or 74%) employ 50 or fewer sworn officers, including 118 (or 34%) employing 10 or fewer sworn officers. Many of these agencies have faced challenges fulfilling all requirements imposed by the Act and aligning their collection practices with the changes introduced since first implementation of the Act. For this reason, some agencies were unable to report complete data responsive to the Community Policing Act for the entire year, and in some cases the quality of the data was limited. Additionally, a substantial number of smaller agencies reported so few traffic stops that it was not possible to interpret data related to driver race/ethnicity. The state may wish to consider providing additional resources to LEAs, particularly smaller agencies, to support their ability to comply with the data-related provisions of the Act.

Another important limitation to the data and findings presented in this report relates to the race/ethnicity data in the Community Policing Database itself. Because the state lacks a standardized mechanism for reporting the race or ethnicity of a given driver, law enforcement officers must either make their own determination about a driver’s race/ethnicity (which may or may not be accurate) or ask for that information in the course of the traffic stop, which could raise constitutional concerns or escalate the perception of conflict in certain situations. Virginia does not collect and store information about a driver’s race/ethnicity, whether in driver-related databases maintained by the Virginia Department of Motor Vehicles or on individual driver’s licenses. Whether and to what extent the data related to driver race/ethnicity in the Community Policing Database accurately captures this information cannot be determined without further review.

The factors described above limited the ability of DCJS staff to conduct any complex statistical analysis of the data or to draw any firm conclusions about the existence and prevalence of the practice of bias-based profiling in a given agency or jurisdiction. It is anticipated that the reporting, analysis, and interpretation of Community Policing Act data will improve in the future as the program matures.

Richmond: Virginia Department of Criminal Justice Services, 2021. 73p.

By Stephanie Seguino, Nancy Brooks, Pat Autilio

This study has three goals. The first it to analyze police behavior as regards race and traffic policing. The second is to evaluate police compliance with the law requiring the collection and reporting of traffic stop data. And the third is to evaluate the effectiveness of the legislation in generating robust data collection on race and traffic policing that is relatively user friendly for analysis by community stakeholders. With regard to the first goal, we examine the data for evidence of racial disparities in several areas: racial shares and magnitudes of stops as well as racial disparities in stop rates, reasons for stops, arrest rates, search rates, and contraband “hit” rates. We also examine trends to determine whether racial disparities fall over time, particularly in response to the legalization of cannabis in July 2018. Our study is based on more than 800,000 traffic stops and 79 Vermont law enforcement agencies. The study includes a number of agencies that had not reported their data in time for our earlier study (Seguino and Brooks 2017). In addition to providing a statewide overview of racial disparities, we compare policing patterns as well as racial disparities across agencies, and separately for municipal law enforcement agencies, sheriff’s departments, and the Vermont State Police. We report raw data on all agencies in our sample, and these results can be found in the appendix. We have been careful to include in the body of the report that follows agency-level statistics only for those agencies that have the minimum number of observations by race (typically, 10 or more). Our main findings are as follows: • The Black and Hispanic shares of stopped drivers exceed their shares of the estimated driving population. The data indicate Black drivers were over-stopped by between 3% to 81%, depending on the measure of the driving population used. Hispanic drivers were over-stopped by 26%. The shares of stops of all other racial groups are at or below their share of the driving population. These numbers represent a statewide average, and obscure wide variation at the agency level. We provide detailed agency-level data in the report, which show that approximately 45 agencies over-stopped Black drivers by more than 25%. • The stop rate per 1,000 residents is very high in Vermont (255 drivers stopped per 1,000 residents) compared to the national average of 86 per 1,000 residents. This overall average obscures notable racial disparities in stop rates. The statewide white stop rate per 1,000 white residents is 256 compared to 459 stops of Black drivers per 1,000 Black residents. The Black stop rate is about 80% higher than the white stop rate and matches the upper bound described above since one of our measures of the driving population of an area is its number of residents. • These averages also obscure the wide variation in stop rates per 1,000 residents. Of particular concern are agencies with large racial disparities in stop rates that also significantly over-stop relative to the national average. For example, in Bennington the overall stop rate per 1,000 residents is estimated to be 659 and Black drivers are over-stopped from 55% to 335% depending on the measure of driving population. • Black and Hispanic drivers were ticketed at a higher rate than white drivers, and Black drivers were also more likely to be given multiple tickets per stop. Our ability to report accurately on ticket rates is limited by data quality concerns as some agencies only report a single outcome per stop even when more than one outcome occurred, such as multiple tickets. • White drivers were more likely to be stopped for moving violations than Black drivers. Black drivers were more likely to experience a stop for vehicle equipment violations. We are concerned that this type of stop may be more investigatory and pretextual than moving violations. Stops that are investigatory/pretextual, based on suspicion of illegal activity rather than observable behavior or evidence, are more susceptible to officer racial bias than stops based on other reasons, such as a moving violation or suspicion of Driving While Impaired (DWI). Several experts have recommended banning this type of stop, which could help to reduce not only racial stop rate disparities but also search disparities. (A November 2019 ruling by the Oregon Supreme Court has banned this increasingly controversial policing practice). • The arrest rate of Black drivers is roughly 70% greater than that of white drivers. The Hispanic-white arrest rate disparity is even larger, with the arrest rate of Hispanic drivers 90% greater than the white arrest rate. Some agency-level disparities were much wider. In Brattleboro, Black drivers’ arrest rate is 400% greater than the white rate; in Colchester, 185% times greater. • Black drivers are about 3.5 times more likely to be searched subsequent to a stop than white drivers and Hispanic drivers are searched at a rate that is 3.9 times greater than that of white drivers. Asian drivers are less likely to be searched than white drivers. Again, some agencies exhibited much wider disparities than the state average. In Brattleboro, Black drivers are almost 9 times more likely to be searched than white drivers; in Shelburne, 4.4 times greater; in South Burlington; 3.9 times greater; in Vergennes, 3.8 times greater; in Burlington, 3.6 times greater; and in Rutland, 3.45 times greater. • Black, Hispanic, and Asian drivers were less likely to be found with contraband than white drivers. The lower hit rate (that is, the percentage of searches that yield contraband) of drivers of color is widely regarded as providing evidence the police rely on a lower bar of evidence to search drivers of color than white drivers, suggesting possible racial bias in the decision to search. In a second test (a logit analysis) for racial bias in searches, we find that the race of the driver continues to be strongly correlated with the officer’s decision to search a vehicle, even after controlling for other factors that may influence the officer’s decision to search a vehicle. • We find that searches based on reasonable suspicion (a lower threshold of evidence than probable cause) have lower hit rates for all racial groups. And, the gap between the (higher) white hit rates and (lower) hit rates for people of color increases. Just as with investigatory/pretextual stops, searches based on reasonable suspicion are more prone to racial bias. With regard to trends over time: • From 2015 to 2019, the number of traffic stops has increased for all racial groups. Sheriff’s Departments registered an 86.4% increase in traffic stops over this time period, compared to a statewide average for all agencies of 39.7%. • Racial disparities in the increase in number of traffic stops are notable. While stops of white drivers increased by 44.6% over this time period, Black stops increased 72.5%; Asian stops, 66.7%; and Hispanic stops, 120.3%. • The share of stops that are investigatory/pretextual, including vehicle equipment stops, increased for all racial groups, but increases were greatest for Black drivers—so much so that by 2019, about one third of all stops of Black drivers were included in this category, up from 23% in 2016. For Hispanics, the increases in the share of such stops was even greater, rising from 18.0% in 2015 to 27.5% in 2019. • Racial disparities in arrest rates have also widened since 2014. The widening gap is due to a decline in the white arrest rate from 2018 to 2019 rather than an increase in the Black arrest rate. • Search rates declined for all racial groups after cannabis legalization but by 2019, the Black search rate continued to be 3 times greater than the white rate. Legalization of cannabis, in other words, did not have a substantial impact on the Black-white search rate disparity. The Hispanic search rate disparity widened from 2018 to 2019 with Hispanic drivers 2.6 times more likely to be searched than white drivers by 2019. • Hit rates have decreased for searches that result in any outcome (warning, ticket, or arrest) but the arrest-worthy hit rate rose slightly from 20.3% to 24.9% from 2018 to 2019. As search rates have fallen, searches appear to be somewhat more productive with regard to those that lead to an arrest but are somewhat less productive overall. Increasing hit rates suggests greater efficiency in policing decisions regarding searches, and clearly, less negative impact on drivers for whom searches are often traumatic experiences. Regarding data quality, our main findings are: • Data quality has improved for some but not all agencies over time. There continues to be a lack of compliance with the legislation requiring race data collection during traffic stops. Missing data on all of the outcomes of a stop, when stops have more than one outcome, date and time of stop, and stops IDs also hinders analysis. • Particularly worrisome is the large number of stops missing race of driver, the main concern of traffic stop data collection. One way to put into perspective the quantity of missing data is to compare the share of stops missing race of driver to the percentage of stops that are of BIPOC drivers. Given the low percentages of people of color in Vermont, even a small amount of missing race data can distort results. For more than a dozen agencies, the percentage of stops missing race of driver is at least double the percentage of stops that are reported to be of BIPOC drivers. At a minimum, this leads to low quality data and the accuracy of results from those agencies. It also violates the spirit of the legislation requiring race data collection. • The legislation has not been sufficiently precise or comprehensive in delineating the data to be collected. Police chiefs have interpreted the meaning of various components of the legislation differently, and thus do not follow a uniform method of reporting data. Some categories of data that would be useful—and are already collected—were not stipulated in the legislation. Law enforcement agencies have as a result declined to share those data. These findings suggest the need to revise the legislation on traffic stop race data collection in order to insure complete data that is uniformly submitted so that it can be analyzed without excessive difficulty.    

Burlington, VT: University of Vermont, 2021. 159p.

By The Crime Research Group

Act 193 mandates that law enforcement agencies collect data on roadside stops for the purpose of evaluating racial disparities. The Act dictates agency data collection and any related conversation centers on agency behavior. The Act and the data collected do not focus on or reflect the stories told by Black, Indigenous and People of Color (BIPOC) as related to their contacts with law enforcement agencies. Because of Vermont’s rural nature, small populations, and policing strategies, we conclude that traffic stop and race data are not sufficient to inform policy makers and stakeholders. Rigorous qualitative research focused on the experiences of the BIPOC community which detects patterns and trends can distinguish structural issues within the criminal justice system. Agency data should be used as a supplement to that research. Part 1 of this report covers the data collection process over the past five years. The purpose of Part 2, which is in a separate report, was to test different methods of assessing racial disparities in traffic stops for their applicability for all Vermont law enforcement agencies.

Montpelier VT: Crime Research Group, 2021. 12p.

By Jeannine Bell and Stephen Rushin

This Article considers how policymakers can more effectively constrain police authority during traffic stops to reduce racial disparities and prevent unnecessary violence.

We begin by chronicling the power granted to police officers during traffic enforcement and the harms generated by this discretionary power. Under existing criminal procedure, police officers have considerable authority to stop motorists for any technical violation of the traffic code, even if the stated justification is a pretext for investigating an unrelated hunch or suspicion. After stopping a motorist, existing doctrine gives police the ability to question motorists, search vehicles under numerous circumstances, arrest drivers for minor violations of the law, and otherwise use traffic stops as a justification for criminal fishing expeditions. This makes police traffic stops an entryway into officer misconduct and violence.

Moreover, the harms of police traffic enforcement are felt disproportionately by communities of color. Empirical evidence generally suggests that Black and Hispanic drivers are more likely than their white counterparts to experience traffic stops. Black and Hispanic drivers are more likely to be stopped during daylight hours relative to nighttime hours when their race is apparent to police through visual observation. And searches of Black and Hispanic motorists are less likely to produce contraband than searches of white drivers, suggesting that police may employ a less rigorous standard of probable cause when justifying vehicle searches of drivers of color.

Given the growing body of literature on the harms caused by police traffic enforcement, some have called for the abolition of police traffic enforcement. Short of abolition, though, this Article shows how jurisdictions across the country have already moved to limit the authority of police during traffic encounters. This approach does not seek to eliminate entirely the police from the enforcement of traffic laws. Rather, it involves state and local policymakers enacting restrictions on police power during traffic enforcement that go beyond those mandated by the U.S. Supreme Court under existing doctrine. Indeed, in recent years, states and municipalities have enacted limitations on the use of pretextual traffic stops, consent searches, and unrelated questioning of motorists after stops. Others have restricted or banned the use of quotas as a police management tool. Some prosecutors’ offices have announced declination policies designed to disincentivize police from using traffic stops as a tool for the investigation of other unrelated crimes. Still other jurisdictions have explored additional reporting requirements and even technological replacements for the use of police officers in the enforcement of the traffic code.

Combined, we argue that this sort of criminal justice minimalism can reduce the harmful and racially disparate effects of police traffic enforcement without compromising public safety

57 Arizona State Law Journal, 2025, 52p.

By Matthew B. Ross

 1. Introduction In November 2021, the New Jersey Attorney General’s Office of Public Integrity and Accountability (NJOPIA) engaged the author of this study for the purpose of conducting an independent analysis of traffic stops made by the New Jersey State Police (NJ-SP). Based on the author’s extensive experience working with state and local policymakers to develop early warning systems for identifying police disparities, the NJ OPIA requested that the analysis focus on the central question of whether there was disparate treatment on the part of NJ-SP towards racial and ethnic minorities.2 After cleaning and linking all of the raw data provided by the New Jersey Office of Law Enforcement Professional Standards (NJ-OLEPS), the analytical sample used in this analysis consisted of 6,177,109 traffic stops made by NJ-SP from 2009 to 2021. In the full analytical sample, 60.52 percent of traffic stops were made of White non-Hispanic motorists while 18.8 percent were Black/African-American and 13.44 percent were Hispanic/Latinx. The overall volume of minority motorists stopped by NJ-SP increased from 35.34 percent in 2009 to 46.28 percent in 2021. The overarching finding from the analysis of the NJ-SP data from 2009-21 is that there was extremely strong evidence of a large and persistent disparity both is the decision to stop as well as the decision to engage in post-stop enforcement like search, vehicular exits, use of force, and arrest. In general, the results were estimated with a very high degree of statistical confidence, survived multiple robustness tests, and were found across most years and troops/stations. In the opinion of this study’s author, these disparities represent strong empirical evidence that NJ-SP is engaged in enforcement practices that result in adverse treatment towards minority motorists. Following best practices, this study applies an ensemble of the most reliable statistical tests available in the scientific literature. The intuition of this approach is that the shortcomings of any individual test are overcome by the totality of the evidence produced by a multitude of tests examining a broad set of enforcement outcomes.

Boston: Northeastern University, 2023. 44p.

By Matthew B. Ross, Jesse J. Kalinowski, Kenneth Barone

Connecticut’s novel approach to collecting and analyz-ing traffic stop data for evidence of disparate treatment is widely considered to be a model of best practice. Here,we provide an overview of Connecticut’s framework,detail solutions to the canonical empirical challenges of analyzing traffic stops, and describe a data-driven approach to early intervention. Unlike most juris-dictions that simply produce an annual traffic stop report, Connecticut has developed an ongoing system for identifying and mitigating disparity. Connecticut's Framework for identifying significant disparities on an annual basis relies on the so-called “preponderance ofevidence” approach. Drawing from the cutting-edge of the empirical social science literature, this approach applies several, as opposed to a single, rigorous empiri-cal test of disparity. For departments identified as having a disparity, Connecticut has developed a process for intervening on an annual basis. In that process, police administrators engage with researchers to conduct an empirical exploration into possible contributing factors and enforcement policies. In Connecticut, this approach has transformed what had once been a war of anecdotes into a constructive data-driven conversation about policy. Variants of the Connecticut Model have recently been adopted by the State of Rhode Island, Oregon, and California. Connecticut’s approach provides a useful model and policy framework for states and localities conducting disparity studies of police traffic stops

Criminology & Public Policy. 2020;19 pages:1289–1303.

By Farhang Heydari

This Article connects the administrative state and the criminal system—two dominant modes of governance that too often are discussed in isolation. It presents an original account of how the policies and the failures of federal administrative agencies drive criminal law enforcement at the local level. In doing so, this Article exposes a significant driver of criminal policy and possible interventions to correct some of its failures. The primary vehicle for this analysis is an in-depth case study of the National Highway Traffic Safety Administration (NHTSA)—the federal agency best known for crash test dummies and five-star ratings as part of its traffic-safety mission—and its support for pretextual traffic stops. This Article unearths a series of NHTSA programs that have, for decades, trained state and local police to use traffic stops to ferret out drug traffickers, violent criminals, and even terrorists. NHTSA’s embrace of a policing mindset has become an unexpected enabler of pretextual stops, one that has pulled agency resources away from systemic regulation of the auto industry. The impact of NHTSA’s quiet campaign has been significant, engraining its view of traffic stops within policing agencies across the country without public visibility or oversight. These revelations come at a critical moment for a nation struggling with twin crises of traffic safety and policing. Learning from NHTSA and moving to the broader administrative state, this Article draws on a diverse set of agencies to identify a pattern of non-law-enforcement agencies shirking their systemic regulatory duties in favor of individual criminal law enforcement. The result is that parts of the administrative state have become systemic drivers of overpolicing and criminalization in ways that have, until now, received virtually no attention.

76 STAN. L.REV. 1 (2024)

By Derek A. Epp & Macey Erhardt

This article asks if investigative police stops (1) help officers find contraband, and (2) serve as a bulwark against violent crime. We focus on the experiences of Fayetteville, North Carolina, which in 2012 mandated that police officers obtain written permission from motorists before conducting searches absent any probable cause. The effect of these mandates was a dramatic reduction in the use of so-called “consent searches.” Using traffic stops data available from the North Carolina Department of Justice, we show that after these reforms went into effect officers made fewer overall searches, but contraband continued to be recovered at pre-reform levels, indicating a reduction in low-quality searches with minimal substantive impact. Moreover, we find that homicide rates are statistically indistinguishable between the pre- and postreform periods. Thus, Fayetteville local government was able to implement community pleasing police reforms without jeopardizing community safety.

POLITICS, GROUPS, AND IDENTITIES https://doi.org/10.1080/21565503.2020.1724160

By Frank R. Baumgartner , Kate Bell, Luke Beyer, Tara Boldrin, Libby Doyle, Lindsey Govan, Jack Halpert, Jackson Hicks, Katherine Kyriakoudes, Cat Lee, Mackenzie Leger, Sarah McAdon, Sarah Michalak, Caroline Murphy, Eyan Neal, Olivia O’Malley, Emily Payne, Audrey Sapirstein, Sally Stanley, and Kathryn Thacker

We evaluate the factors associated with an officer’s decision to search a driver or vehicle after a routine traffic stop, and we compare the accuracy of these searches by looking at the share leading to arrest. Racial disparities in search rates by race and gender of driver are similar for all types of officers; all tend to search Black male drivers at higher rates than any other demographic. White male officers have higher search rates for all types of drivers. Further, they conduct the greatest share of “fruitless searches” (those not leading to arrest), and these searches are particularly targeted on those drivers with the greatest number of cumulative disadvantages

Policy Studies Journal, Vol. 49, No. 3, 2021

By Jeffrey A. Fagan and Amanda B. Geller

Following Soto v. State (1999), New Jersey was the first state to enter into a Consent Decree with the U.S. Department of Justice to end racially selective enforcement on the state’s highways. The Consent Decree led to extensive reforms in the training and supervision of state police troopers, and the design of information technology to monitor the activities of the State Police. Compliance was assessed in part on the State’s progress toward the elimination of racial disparities in the patterns of highway stops and searches. We assess compliance by analyzing data on 257,000 vehicle stops on the New Jersey Turnpike by the state police from 2005– 2007, the final months of the Consent Decree. Specifically, we exploit heterogeneity of officer and driver race to identify disparities in the probability that stops lead to a search. We assume a crime-minimizing or welfarist rationale for stops, under which race-neutral factors are equally likely to motivate stops, regardless of driver or passenger race. We also test a Fairness Presumption by comparing search patterns between driver-officer pairs where the driver and officer are different races, and a set of race-neutral benchmarks where the driver and officer are the same race. Results of fixed effects logistic regressions show that Black and Hispanic drivers, when stopped, are more than twice as likely as White drivers to be searched, regardless of officer race. The results also suggest that search patterns vary significantly by officer race: Black officers are less likely to conduct a search in the course of a stop than are White drivers. We also see significant interactions between the race of officers and that of the drivers they stop: Black drivers are significantly more likely to be searched by White officers than they are by Black officers; on the other hand, Hispanic drivers are significantly less likely to be searched by either Black or White officers than they are by Hispanic officers. Racial disparities in the selection of stopped drivers for search and in the rates of seizure of contraband suggest that despite institutional reforms under the Consent Decree in management and professionalization of patrol officers, there were no tangible gains in distributional equity. We review the design of the Consent Decree and the accompanying oversight mechanisms to identify structural weaknesses in external monitoring and institutional design in the oversight of the State Police that compromised the pursuit of equality goals.

J. SOC. POL'Y & L. 16 (2020). Available at:

By New York University School of Law, Policing Project

In response to the Gideon’s Army report indicating racial disparities in traffic stops, and the shooting of Jocques Clemmons, the Nashville Mayor’s Office asked the Policing Project to help develop strategies to address the disparities and improve community-police relations in Nashville. The Policing Project is an organization devoted to front-end democratic accountability to assure just and effective policing. The Policing Project talked with dozens of Nashville residents about their experiences with policing. Based on those conversations, we proposed to conduct a thorough assessment of the costs and benefits of using traffic stops to address crime. And we suggested that the City create a Steering Committee to guide work around community-police engagement and policing in Nashville. We conducted the traffic stop data work in collaboration with the Stanford Computational Policy Lab (SCPL), whose researchers performed the analysis. (The SCPL team’s more detailed report is included here as Appendix B.) The Metropolitan Nashville Police Department (MNPD) provided the necessary data, and has from the beginning shown a strong commitment to re-evaluating its traffic stop strategies and developing alternatives that can achieve public safety with fewer social costs. As the SCPL report shows, and as we summarize below, there are indeed notable racial disparities in traffic stops in Nashville. These disparities are higher for traffic stops around non-moving violations, such as broken taillights or expired tags. Disparity, however, is not necessarily evidence of discrimination. Any number of neutral factors, including officer deployment patterns or differences in rates of offending, may explain these and other disparities in the criminal justice system. MNPD explains these racial disparities in traffic stops on the ground that officers go where the crime is, and that in Nashville, high-crime neighborhoods tend to have larger minority populations. The SCPL analysis bears this out. However, even controlling for crime, unexplained racial disparity still remains. More importantly, the SCPL report shows that traffic stops are not an effective strategy for reducing crime. In particular, MNPD’s practice of making large numbers of stops in high crime neighborhoods does not appear to have any effect on crime. We make a number of recommendations, including that MNPD: • reduce the number of traffic stops • acknowledge black residents have been disproportionately affected by MNPD’s stop practices • monitor racial disparities on an ongoing basis • redeploy officer resources toward more effective crime-fighting tools • consider adopting a Neighborhood Policing strategy • post its department policies online • conduct a review of certain key policies such as use of force • conduct a review of training around use of force, traffic stops, and procedural justice • adopt a body camera policy with attention to transparency regarding the release of body camera footage In addition, we suggest that Nashville engage in a public process of strategic planning around public safety, bringing together the voices of the community and MNPD officials in doing so.

New York: Policing Project, 2023. 27p.

By Seleeke Flingai, Mona Sahaf, Nicole Battle, and Savannah Castaneda

The murder of George Floyd in May 2020 spurred a national reckoning around how Black people are viewed and treated by law enforcement and the criminal legal system. Some elected officials, prosecutors, and police have acknowledged their moral responsibility to pursue racial justice by examining racial disparities and inequities. This report addresses one such practice—non-traffic-safety stops. These occur when police stop and detain people for minor traffic violations that pose no identifiable risk of harm to people outside of the vehicle. Vera partnered with the Suffolk County (Massachusetts) District Attorney’s Office from July 2020 to March 2022 to study racial disparities in the criminal legal system. Vera’s analysis revealed that non-traffic-safety stops in Suffolk County are worsening racial disparities in traffic enforcement. This report shares findings from Vera’s analysis, along with proposed solutions that prohibit or deter such stops.

New York: Vera Institute of Justice 2022. 37p.

Katie Blum and. Jill Paperno

In recent years our country has faced a racial reckoning. One of the areas of focus has been racial bias in policing. In the following pages we will address the law enforcement practice of pretext stops – stopping individuals for a reason that may not be lawful but using a low-level traffic or other violation to justify the stop. The following report is our working draft of what will later be released as a comprehensive review of pretext stops in New York. In the coming months, Empire Justice Center will be gathering more information and feedback that will be incorporated into later reports. In Section III, the Introduction to this Report, we recognize that of the approximately 1,000 deaths of civilians during police-civilian encounters each year, approximately 10% occur during low-level traffic stops. We explain what pretext stops are, and how they came to be an integral part of modern policing. We preview the harm caused by pretext stops, further discussed in Section VII. In Section IV, Racial Bias and the Data, we review information gleaned from numerous studies, as well as two books – Pulled Over: How Police Stops Define Race and Citizenship, by Charles Epp, Donald Haider and Steven Maynard-Moody, and Suspect Citizens: What 20 Million Traffic Stops Tell Us about Policing and Race, by Frank Baumgartner, Derek Epp and Kelsey Shoub. These sources demonstrate that pretext stops are executed far more frequently on People of Color, with most studies focusing on Black and white drivers. Additionally, once stopped, Black drivers are more likely to be searched than white drivers. In Section V, The Law and Pretext Stops, we explain the cases that have led to the conclusion that absent proof of discriminatory intent on the part of a law enforcement officer, a high bar to reach, pretext stops are lawful. In Section VI, The Community Safety Question, we address findings that pretext stops provide minimal enhancement of community safety, reviewing studies that have addressed the frequency of seizure of contraband, as well as arrests and charges of individuals stopped. In Section VII, The Harms Caused by Pretext Stops, we consider whether these minimal community safety benefits are worth the many harms caused by pretext stops – racial disparities in how policing occurs, civilian deaths, officer deaths, and the resulting lack of trust in law enforcement and the criminal justice system. In Section VIII, Pretext Stops in Rochester, N.Y., we focus on the types of offenses that are the basis for some pretext stops in Rochester, New York, a city that has faced rising tension and civilian opposition to policing in recent years, and the racial disparities as well as geographic disparities in where these stops occur. We also review some of the statements and implicit recognition of racial disparities in policing by community leaders who have considered pretext stops.

Albany, NY: Empire Justice Center, 2023. 71p.

By David S. Abrams, Hanming Fang and Priyanka Goonetilleke

Police “stop-and-frisks” of pedestrians and motorists have become an increasingly controversial tactic, given low average rates of contraband discovery, incidents of abuse, and evidence of racial disparity. Study of the tactic by economists has been much influenced by Knowles, Persico, and Todd (2001; hereafter, KPT) who first suggested the use of a “hit rate” (contraband discovery rate per frisk) test to distinguish racial prejudice from statistical discrimination in highway searches by police officers. Models used by KPT and almost all subsequent literature (e.g., Anwar and Fang 2006) on the subject imply diminishing marginal returns to frisks. That is, if frisks decrease substantially, the rate of contraband discovery should rise, ceteris paribus. This is the first paper to test this assumption empirically using arguably exogenous variations in frisk rates (cf. Feigenberg and Miller 2022). 1 We study the period around the nationwide protests that followed the killing of George Floyd on May 25, 2020, after which police frisks dropped tremendously and rapidly. Using extremely granular data from Chicago, we find that hit rates increased as police frisks plunged, in line with the predictions of KPT.

AEA Papers and Proceedings 2022, 112: 178–183 ,2022. 7p.

By Travis Carter, Jedidiah Knode and Scott Wolfe  

This report presents the results from a racial/ethnic disparity analysis of Michigan State Police (MSP) traffic stops conducted in 2021. The goal of the analysis is to identify the extent of racial/ethnic disparities in MSP traffic stop behavior across MSP worksites (i.e., posts). The analyses are based on a leading empirical approach to assessing racial/ethnic disparities in traffic stop behavior—the veil-of-darkness (VOD). The analyses account for important structural differences across posts and their jurisdictions, such as the rate of violent crime and troopers per capita, as well as temporal factors that may shape traffic patterns and stop behavior (e.g., time of day, day of week) to help ensure the results are as informative as possible. Below, we briefly outline the methodology employed and summarize the main findings. When discussing the results from this report, it is important to recognize the difference between “disparity” and “discrimination.” Disparity in these traffic stop analyses refers to differences in racial/ethnic group representation based on presumed visibility of the driver. Disparity cannot identify intent, whereas discrimination inherently involves intent. Therefore, discrimination in traffic stop behavior refers to police officers intentionally stopping individuals based on their status in a racial/ethnic minority group. Discrimination can generate disparities by way of differential treatment of racial/ethnic groups, but disparities may also be the result of nondiscriminatory (e.g., environmental, situational, etc.) factors such as crime prevalence and driving pattern differences. This report and its findings can speak only to the extent of racial/ethnic disparity in MSP traffic stops. The data cannot ascertain whether racially discriminatory practices are occurring within MSP. Although disentangling disparity from bias is critical towards improving police practices, accurately identifying the existence of such disparity and its magnitude is an important precursor to this process. More information on the data collection process is provided in the body of the report. Next, we highlight the main takeaways from the analyses.   

East Lansing:  Michigan Justice Statistics Center School of Criminal Justice Michigan State University, 2022. 33p.

By Gabrielle T. Isaza, Robin Engel and Jennifer Calnon Cherkauskas 

Sobering centers offer a unique opportunity to reduce arrests for vulnerable populations while removing a person from a potentially dangerous situation. Despite the long and complex history of their use, little is known systematically about the effectiveness of sobering centers as an alternative to arrest. Only a handful of studies have examined the impacts of sobering centers on the criminal justice system, and these studies typically focus on a single site. To build the evidence on sobering centers, Arnold Ventures funded our research study assessing the utility of sobering centers as an alternative to arrest. This report is the first in a series detailing our multi-method and multi-site research study, launched in January 2020. In this research study, examine four primary research questions: 1. What are the patterns of policies and practices for police use of sobering centers as an alternative to arrest? What guides this decision-making? 2. What are the situational factors police use in practice to determine whether or not to use sobering centers as an alternative to arrest? 3. How do police balance and overcome policy and legal inconsistencies guiding the transport to and use of sobering centers? 4. When individuals are sent to sobering centers in lieu of arrest, does it alter their relative risk of recidivism or future contact with police? This report focuses on the quantitative findings of Phase I, disclosing the results of two national surveys—one for law enforcement agencies and one for sobering center facilities. Survey findings shed light on how police use sobering centers and the perceived benefits and barriers to their use. In turn, the survey findings also provide important insights on how to build effective partnerships and enhance the utility of sobering centers as an alternative to arrest.  

Arlington VA: National Policing Institute, 2022. 78p.

By Robin S. Engel,  Jennifer Calnon Cherkauskas, Nicholas Corsaro, Murat Yildirim

In 2002, the Pennsylvania State Police (PSP) was one of the first state police agencies to initiate traffic stop data collection voluntarily. The current data collection effort is based on foundational work conducted with the same research team for more than a decade, beginning with initial planning in 1999. After discontinuing the data collection program in 2011, the PSP renewed its traffic stop data collection effort in 2021, which now continues in partnership with the National Policing Institute (the Institute). Given the variety of factors involved in police stop and enforcement decisions, it is beneficial for agencies to identify and better understand trends and patterns to enhance their ability to interact with the public safely and fairly. The voluntary collection and analysis of traffic stop data is consistent with recommended best practice, demonstrates dedication to transparency and accountability to the public, and continues the PSP’s commitment to evidence-based policing practices. This report documents the findings from statistical analyses of data collected during all member-initiated traffic stops by the PSP from January 1, 2022 – December 31, 2022. These data are reported by individual troopers after each member-initiated traffic stop, gathered and compiled by the PSP, and transmitted weekly to the Institute’s research team. Throughout each section of this report, information is presented at multiple organizational levels, reflecting the PSP’s organizational structure consisting of four Areas, 16 Troops, and 88 Stations. Presenting information in this manner illustrates differences and similarities across organizational units. It permits the identification of organizational and geographic groups that may appear as outliers, providing opportunities for closer examination and focused attention by PSP officials.  

Arlington, VA: National Policing Institute, 2023. 169p.

By Shelley Hyland, Lynn Langton and Elizabeth Davis

This report presents data on the threat or use of nonfatal force by police against white, black, and Hispanic residents during police contact. This report describes the characteristics of the contact, the type of force threatened or used, and the perceptions that force was excessive or the police behaved properly during the contact. It also examines trends in the threat or use of force and the relationship between officer and driver race and Hispanic origin in traffic stops involving the threat or use of force. Data are from the 2002, 2005, 2008, and 2011 Police- Public Contact Surveys, which were administered as supplements to the National Crime Victimization Survey.

Washington, DC: U.S. Department of Justice Office of Justice Programs Bureau of Justice Statistics, 2015. 17

By Magnus Lofstrom, Joseph Hayes, Brandon Martin, and Deepak Premkumar

Stark racial inequity has long been a deeply troubling aspect of our criminal justice system. In recent years, traffic stops have emerged as a key factor driving some of these inequities and an area of potential reform. Are there opportunities to identify kinds of traffic stops that could be enforced in alternative ways—potentially improving officer and civilian safety, enhancing police efficiency, and reducing racial disparities—without jeopardizing road safety?

To explore this question, in this report we use data on 3.4 million traffic stops made in 2019 by California’s 15 largest law enforcement agencies to examine racial disparities in stop outcomes and experiences across time of the day, type of law enforcement agency, and type of traffic violation.

San Francisco: Public Policy Institute of California, 2022. 29p.