You are currently viewing Racial Disparities in Law Enforcement Stops

Racial Disparities in Law Enforcement Stops

  • Post author:
  • Post category:Daily News

Key Takeaways

Racial disparities within the criminal justice system continue to be a pressing issue for the US and California. In the wake of the killing of George Floyd, discussions around police reforms have heightened and centered on how law enforcement engages with people of color.

In this report, we analyze data for almost 4 million stops by California’s 15 largest law enforcement agencies in 2019, examining the extent to which people of color experience searches, enforcement, intrusiveness, and use of force differently from white people. While it is important to caution the reader that analysis of these differences is not causal, our analysis—which focuses in particular on differences between Black and white Californians—reveals notable differences.

  • Black Californians are more than twice as likely to be searched as white Californians, at about 20 percent versus 8 percent of all stops. 
  • Searches of Black civilians are somewhat less likely to yield contraband and evidence than searches of white civilians. Overall, searches yielded contraband or evidence in about one-fifth of all searches. 
  • Black people are overrepresented in stops not leading to enforcement—defined as an officer declining to issue even a warning—as well as in stops leading to an arrest. 
  • Black individuals are almost twice as likely to be booked into jail as white individuals. 
  • While differences in locale and context for the stop—such as when an officer has knowledge of an outstanding warrant—significantly contribute to racial disparities, notable inequities remain after accounting for such factors.

These disparities are driven primarily by traffic stops made by the 14 data-contributing police and sheriff departments (as compared with the California Highway Patrol). These findings can provide guidance for discussing which stops can safely be reduced to mitigate racial inequities, which may also reduce risks and injuries to both officers and civilians.

Introduction

While the nation grappled with the greatest public health crisis in at least a century—a pandemic in which communities of color carried the heaviest burden—the killing of George Floyd, among others, sparked civil unrest around California and the country. This unrest further highlighted stark racial inequities in our criminal justice system and the need for reform.

Inequities are especially stark between Black and white individuals: while Black residents make up about 6 percent of California’s population, roughly 16 percent of all arrests are of Black residents. Disparities are even greater at later stages in the criminal justice process, where Black people account for about 25 percent of county jail populations, about 26 percent of the probation population, and 29 percent of the prison population.

recent PPIC survey found that 62 percent of Californians believe that the criminal justice system is biased against African Americans. Among African Americans, 88 percent hold this view. And while 54 percent of adults in California say police treat all racial and ethnic minorities fairly “almost always” or “most of the time,” only 18 percent of African Americans share that view.

Recognizing the need for data and research on law enforcement stops, the California legislature passed the Racial and Identity Profiling Act (RIPA) in 2015. The legislation—which was rolled out in waves based on the size of the agency—will require all law enforcement agencies in California to collect officer-perceived demographic and other detailed data for all pedestrian and traffic stops by 2023. The most recent data available include nearly 4 million stops made in 2019 by the 15 largest law enforcement agencies in the state.

This report builds on our previous work on arrests in California that found that criminal justice reforms implemented over the last decade have reduced racial disparities in arrests, bookings, and incarceration (Lofstrom et al. 2020; Lofstrom, Martin, and Raphael 2020). However, wide gaps remain. Here we broaden the scope to law enforcement stops, which include the many interactions Californians have with law enforcement that do not lead to arrests.

Complementing the 2021 RIPA Board report, we analyze the most recent stop data to better understand how interactions with law enforcement vary across race and ethnicity. Given that the starkest disparities are between Black and white Californians, our research focuses on inequities between these groups in frequency of stops, reasons for stops, and outcomes to provide a more complete picture of what those experiences are like.

We examine the likelihood that the individual stopped is searched, whether the search yielded any contraband or evidence, and if the stop resulted in any enforcement measures. We also examine intrusiveness and use of force, measured by reported outcomes such as being asked to step out of the vehicle, being handcuffed, and the involvement of an officer’s weapon. We then separately analyze outcomes by statewide (California Highway Patrol) and local (police and sheriff’s departments) jurisdictions.

RIPA Data on Police Stops

The California state legislature passed the Racial and Identity Profiling Act (RIPA) in 2015 (AB 953), which requires all law enforcement agencies in California to collect perceived demographic and other detailed data regarding all pedestrian and traffic stops by 2023 (see Technical Appendix A for more details). “Stop” is defined as any detention by a peace officer of a person, or any peace officer interaction with a person in which the officer conducts a search.

The data elements mandated by statute include person-level and stop-level information. For person-level data, which we refer to throughout as personal traits, officers are required to record their perception of the identity characteristics for each individual stopped, including

  • race or ethnicity
  • gender
  • approximate age
  • lesbian, gay, bisexual, or transgender (LGBT) status
  • English fluency
  • disability (including behavioral health status)

Officers are prohibited from asking the person stopped to self-identify these characteristics.

Stop-level elements include

  • reason for stop (including a traffic violation, reasonable suspicion, parole/probation/mandatory supervision, knowledge of outstanding arrest warrant/wanted person, and consensual encounter resulting in search)
  • action taken by officer during stop (such as suspect removed from vehicle, removed from vehicle by physical contact, curbside detention, handcuffed, canine search, use of electronic device, chemical spray, or use of firearm)
  • reason for search (probable cause, consent, search warrant, visible contraband, odor of contraband, etc.)
  • contraband or evidence discovered (such as guns, drugs, drug paraphernalia, alcohol, money, or stolen property)
  • enforcement result of stop (including no action, warning, citation, cite and release, and booking)

The data do not allow for corroborating the accuracy of the reported information, including the race and identity of the individual stopped and the specific actions taken by the officer. Nor do the data include information on the race and ethnicity of the officer.

We examine the most recent available data from the 15 law enforcement agencies who submitted their first full year of stop data from 2019. This includes California Highway Patrol (CHP), eight police departments (Los Angeles, San Diego, San Francisco, Sacramento, Fresno, San Jose, Long Beach, and Oakland) and six county sheriff’s departments (Los Angeles, San Bernardino, Sacramento, San Diego, Riverside, and Orange County).

These agencies recorded 3,992,074 stops of motorists and pedestrians during the 2019 calendar year. Technical Appendix A provides details and a discussion of how the distribution of stops and outcomes vary across agencies.

Disparities in Stops and Reasons for Stops

A primary objective of this report is to examine disparities between the experiences and outcomes Black and white Californians have during a stop. To start, we examine racial disparities in the frequency of being stopped by law enforcement, and disparities in the reported reason for the stop.

When we compare shares each group represents in stops to shares by population, we find considerable disproportionality statewide. Black residents accounted for 16 percent of stops made by all participating law enforcement agencies during 2019 (Figure 1) but constituted only 7 percent of the state’s population.(1) Residents identified by law enforcement as Middle Eastern or South Asian were also overrepresented in stops (5%) compared to their share of the state’s population (2%).

White residents were represented fairly proportionally in stops (33%), compared with their population share (34%), as were Latino residents (39% and 41%, respectively). Asian individuals were underrepresented in stops (6%) compared with their share of the population (12%), as were multiracial residents (1% and 3%, respectively).

Individuals identified as Pacific Islanders were overrepresented (0.5% of stops, compared with 0.3% of the population), and those identified as Native American were underrepresented (0.2% and 0.3%, respectively). The percentage-point differences are small, but as a proportion of the population share, these differences are considerable. Again, the racial/ethnic identification comes solely from the officer making the stop.Figure 1

Black residents are overrepresented in police stops

figure 1 - Black residents are overrepresented in police stops

SOURCES: Author calculations using California Department of Justice, Racial and Identity Profiling Act (RIPA) Wave 2 data, 2019; RIPA Board Report 2021 population calculations using American Community Survey (2018).

The data also reveal differences between reasons for stopping people of different races. For example, while more than 90 percent of stops of individuals perceived to be Asian or of Middle East/South Asian origin are stopped for traffic violations, about 75 percent of Black Californians stopped are for traffic violations (Figure 2). Conversely, officers report reasonable suspicion in 21 percent of stops of Black people, while 11.7 percent of white people and 5.6 percent of Asian people are stopped for reasonable suspicion.

While fewer stops involve individuals known by the officer to be on parole or probation or to have an outstanding warrant, their status provides officers with rights to stop and search without consent or reasonable suspicion. The percent of Black residents stopped who are on parole or probation is twice that of white residents (1.2% vs. 0.6%), and it is notably higher than Latino (0.8%) and Asian (0.2%) residents stopped as well.

The share of stops for an outstanding warrant is also twice as high for Black compared to white residents, also at 1.2 percent versus 0.6 percent. Technical Appendix Table A2 details differences across race and ethnicity in officer-perceived gender, age, mental health status, and whether the officer was responding to a call for services.Figure 2

A greater share of Black people than white people are stopped for reasonable suspicion

figure 2 - A greater share of Black people than white people are stopped for reasonable suspicion

SOURCE: Author calculations using California Department of Justice, Racial and Identity Profiling Act (RIPA) Wave 2 data, 2019.

Differences in Stop Experiences

A key way this report extends the 2021 RIPA Board report is by taking a closer look at racial disparities in the experiences and outcomes of individuals after they are stopped by law enforcement. More specifically, we analyze the following four stop outcomes:

  • likelihood the individual stopped was searched;
  • likelihood contraband or evidence (weapons, property, drugs or other, such as alcohol or cell phones) were found, if the person was searched;
  • likelihood of enforcement, hierarchically defined below:
    • at least a warning was issued;
    • at least a citation (for an infraction, such as a speeding ticket) was issued;
    • an arrest (cite and release or booked into jail); or
    • booked into jail.
  • likelihood of experiencing intrusive action or use of force, hierarchically defined below:
    • at least asked to step out of the vehicle;
    • at least some physical contact (such as removed from car);
    • at least detained (curbside or patrol car);
    • at least handcuffed;
    • involved an officer’s weapon (such as aiming a firearm, but not necessarily firing the weapon); or
    • officer weapon used (including use of firearm, electronic device, chemical spray, or baton).

Of the almost 4 million reported stops in 2019, slightly more than 452,000 led to a person or property being searched. In close to 97,000 of those searches—about 21 percent—the officer found some contraband or evidence. That is, officers found contraband or evidence in about 2.4 percent of all police stops (Table 1).

The most common contraband was drugs or drug paraphernalia, found in a little more than 60,000 searches. The second most common category is other, which includes alcohol and cell phones (presumably evidence). In 18,507 searches, the officer found a weapon or ammunition. In more than 11,000 instances, the officer found property, which includes money that was either illegally held or was evidence.

In the vast majority of stops, about 88 percent, the officer issued at least a warning (Table 1). The officer issued at least a citation in 64 percent of all stops. Officers made an arrest—either a cite and release, or a booking—in 11 percent of stops, and booked over 6 percent of stopped individuals into jail.

While most stops led to some level of enforcement, intrusive actions were less common: for example, individuals were at least asked to step out of the vehicle in about one in six stops. Officers report some physical contact in over 14 percent of stops, most of which involved detaining a person curbside or in the patrol car.

In about 8 percent of stops, the person was at least being handcuffed. The percentage of stops that involved an officer’s weapon (which captures an officer pointing a firearm as well as when the officer uses the firearm or other weapon) is relatively small, at 0.42 percent. However, while the percentage is small, there are 16,918 stops where the officer reports that their weapon was involved. In 1,930 instances (0.05% of stops), the officer used a weapon— meaning the officer discharged a firearm or electric device such as a Taser, used a chemical spray or a baton, or a canine bit the stopped individual. The stop data do not capture whether anyone was injured as a result of the use of a weapon, or any other action taken during the stop.Table 1

Post-stop outcomes, all 15 law enforcement agencies, 2019

table 1 - Post-stop outcomes, all 15 law enforcement agencies, 2019

SOURCES: Authors calculations using California Department of Justice, Racial and Identity Profiling Act (RIPA) Wave 2 data, 2019.

Black Californians are notably overrepresented in police stops, and officers report reasons for stops that can vary across race and ethnicity, and across law enforcement agencies. We next consider the role of context of a stop, in an effort to better understand underlying factors to the patterns observed in outcomes.

Differences in Context of Stops

California passed the RIPA legislation in 2015 based on concerns about bias in policing that leads to different groups having different experiences with law enforcement. Beyond mandating collection of stop data, the legislation expanded and clarified the definition of racial and identity profiling to consider and rely on protected group status, such as race and ethnicity, in “… deciding which persons to subject to a stop or in deciding upon the scope or substance of law enforcement activities following a stop…”

Research consistently finds evidence of racial bias, explicit and/or implicit, broadly in society (see for example Bertrand and Mullainathan 2004; Bayer et al. 2017; Rothstein 2017; Avenancio-Leon and Howard 2019; Chetty et al. 2020; Kline, Rose, and Walters 2021). Furthermore, research has also found racial discrimination within the criminal justice system in jury, judge, and prosecutor decisions (Anwar, Bayer, and Hjalmarsson 2012; Arnold, Dobbie, Yang 2018; Sloan 2019). It is perhaps unsurprising that these racial biases extend to policing (Fryer 2019; Luh 2019; Hoekstra and Sloan 2020; Ba et al. 2021; Feigenberg and Miller 2021; Goncalves and Mello 2021), providing support to concerns historically raised by communities of color—concerns renewed in the wake of the killing of George Floyd.

Many factors contribute to whether an officer stops someone and to the officer’s subsequent actions. And while the RIPA data quite strongly point toward differences in stop outcomes across race and ethnicity (RIPA Board Report 2021), these differences may echo circumstances that do not reflect an individual officer’s bias. The reason and context for the stop likely influence an officer’s decisions and actions—for example, an officer may simply warn a driver stopped for speeding. Hence, differences in stop experiences between Black and white people may reflect differences in the reasons for the stop (Figure 2).

Independent of race and ethnicity, if an officer observed a person committing a crime, if a person has a warrant, or has a weapon, that person likely will be detained and searched, and possibly booked into jail after a stop. Such situations may be more adversarial—including the potential for use of force—than a traffic stop. If an individual is acting erratic, possibly due to behavioral health issues, an officer may shift decisions and actions. The prevalence of such situations across race and ethnicity may contribute to differences in outcomes.

Additionally, younger/inexperienced drivers may be more likely to violate traffic laws, and hence are plausibly more likely to be stopped than older and more experienced drivers. With men and adolescents/younger adults engaging in relatively more criminal activity, officers may place more scrutiny on younger men when they are stopped than on older individuals or women, independent of race/ethnicity (e.g., Ulmer and Steffensmeier 2014).

On average, Black Californians stopped by law enforcement are perceived to be younger compared to white Californians who are stopped (Technical Appendix Table A2). People stopped are also more often males. Relatively higher shares of Black persons are stopped for reasonable suspicion, outstanding warrant for an arrest, or mandatory supervision of a parolee/probationer. The latter two categories make a search more likely, as a warrant for a search is not needed, nor is cause, in California. Officers also report visibly seeing contraband in a higher share of stops of Black people than of white people.

Among the 15 largest law enforcement agencies, California Highway Patrol made more than 60 percent of all stops in 2019 of white individuals, but only about 35 percent of stops of Black individuals. And while Los Angeles Police Department (LAPD) accounts for almost 31 percent of stops of Black Californians, the agency made only 10 percent of stops of white Californians; partly reflecting that a higher share of the Los Angeles population is Black (about 8%) compared to statewide (about 6%). Agency-level differences in policing strategies, missions and roles, as well as officer behavior and biases, are also possible contributing factors.

Accounting for Differences in Personal Traits and Contexts

Differences in contexts, location, and agencies likely contribute to racial disparities in stop outcomes. Our goal here is to use regression models that adjust to account for differences across race/ethnic groups in such factors, and move us towards more “apples-to-apples” comparisons.

That is, we seek to compare stop outcomes across race/ethnicity for, say, individuals of the same age and gender, stopped for the same reasons by a given law enforcement agency. We also adjust for whether the officer reported seeing contraband, and whether the person had an outstanding warrant or is on parole or probation. (See Technical Appendix B for a detailed discussion of the analysis and regression model.)