Traffic stops are among the most common interactions the public has with the police, and these stops, especially pretextual stops, can lead to various negative consequences. Compared with moving violations, which are more focused on improving public safety by responding to speeding, running red lights, and other actions that put pedestrians and other motorists in danger, pretextual stops occur when law enforcement officers pull over vehicles for minor traffic violations, such as broken taillights or failure to signal, but use the stops as a pretext to investigate unrelated suspected illegal activities, such as drug or weapons possession. The practice has sparked significant debate and controversy because of the potential for abuse and concerns about racial profiling and civil liberties.

Pretextual stops can escalate tensions and result in unwarranted searches, frisks, fines, and arrests; they can also lead to emotional distress, loss of productivity owing to lengthy stops, and in too many cases, physical harm or death for the people stopped. And the impact of these stops goes beyond these immediate inconveniences, affecting community-police relationships and perpetuating social inequities. Research on pretextual stops highlights that these stops disproportionately target Black and brown people, increasing their distrust and fear of law enforcement. Studies also indicate that they contribute to systemic issues of racial profiling.

Community groups can highlight how traffic stops exacerbate racial inequities by making data on these stops more accessible to residents so they can hold the police accountable. Equipped with statistics, people can call for policies that mitigate biases in law enforcement interactions and reduce the harms done by the criminal legal system. Two local groups participating in the Catalyst Grant Program demonstrate how data access and understanding can be leveraged to motivate change. These examples can inspire groups in other places to use data to advance reform and equity in the criminal legal system.

Using Traffic Stop Data to Influence Policy

In the Bay Area, traffic enforcement has harmed certain communities more than others. Black and Latinx/e drivers are disproportionately stopped and ticketed by police officers for traffic infractions compared with white and Asian drivers. Officers issue millions of tickets a year and levy billions of dollars in fines and fees against Black and Latinx/e drivers that affect their economic well-being. SPUR, a 2022 Catalyst grantee, worked with the Coalition to End Biased Stops to address these issues.

Through its Catalyst grant project, SPUR conducted a deep dive into how traffic stop practices were affecting marginalized communities in San Francisco, Oakland, and San Jose, California. Using data from the 2019 Racial and Identity Profiling Act and the 2019 American Community Survey, it analyzed the number and rate of traffic stops and their outcomes, disaggregating the results by drivers’ race, ethnicity, and gender. It found that while Black and Latinx/e people accounted for only 5 and 15 percent of San Francisco’s population, respectively, they each experienced 19 percent of police traffic stops there. To show that many of these stops were not related to violent acts, SPUR also looked at why the stops were made, limiting its analysis to moving violations, equipment violations, and nonmoving violations through the same lenses of race, ethnicity, and gender. It found that Black and Latinx/e drivers were more likely than drivers of other races to be stopped for equipment or nonmoving infractions, such as having a broken taillight or not having their registration. It is also important to note that California has some of the most expensive traffic citations in the US, adding to the disparate burden on Black and Latinx/e communities in San Francisco.

SPUR’s research sheds light on local disparities in San Francisco, and because of its work with the Coalition to End Biased Stops, it was able to educate and engage policymakers with its findings. Its efforts culminated in the San Francisco Police Commission requiring (PDF) that the San Francisco Police Department make all police stop data accessible to the public in a machine-readable format online. This change enables the general public access to data on all police stops. Further, SPUR’s economic justice policy director, Jacob Denney, presented to the commission on traffic stops and pretextual stops in San Francisco, leading to San Francisco ending pretextual traffic stops and limiting enforcement of nine minor traffic violations. This means police officers cannot conduct traffic stops for these nine minor violations unless they meet specific criteria. Estimates (PDF) reveal these changes should result in at least 10,000 fewer traffic stops a year in the city of San Francisco and avoid an estimated $830,000 in fines and fees. SPUR’s data analysis was vital in gaining sufficient support from the San Francisco Police Commission to enact this significant and meaningful policy change.

Advancing Data Tools to Expand Organizational Capabilities

The Defender Association of Philadelphia analyzed traffic stops in Philadelphia and found glaring racial biases, spurring the creation of the city’s Achieving Driving Equity Ordinance, enacted in March 2022. The legislation bars Philadelphia police officers from pulling over drivers for eight low-level motor vehicle code infractions, and it requires the Philadelphia Police Department to provide detailed public data on all traffic stops. Following this work, the Defender Association leveraged the Catalyst Grant Program to expand its data analytics and software engineering capacities to create a public data dashboard of traffic stops in Philadelphia. The association’s Police Accountability Unit translated its previous data cleaning and analysis into the Python programming language, increasing flexibility across variables and time frames. During the project, it also crafted new code to connect to various public datasets’ application programming interfaces, enabling the creation of interactive dashboard visualizations using real-time data. The collaborative efforts of the team and the introduction of a new codebase serve as the foundation for the organization's data dashboard.

The organization's dashboard is intended to make Philadelphia Police Department vehicle stop data (available at OpenDataPhilly, a catalog of open data in Philadelphia) more accessible and transparent. The dashboard presents the data through relatable questions and narratives, avoiding the need for users to download and decipher patterns from millions of vehicle stops. Users will navigate through straightforward questions such as how frequently police vehicle stops occur in their neighborhood and whether the police treat people and neighborhoods differently. The dashboard will provide interactive graphs, maps, and data sentences as responses, accompanied by tooltips for more detailed explanations. It also includes information about the history of the Driving Equality legislation, addressing common questions and providing answers about the underlying data. The open-source Python code for the dashboard is available on the code-sharing platform GitHub, ensuring transparency and encouraging collaboration.

Data can be difficult to obtain even when they are required to be provided by law. To comply with the Driving Equality companion data law, the Philadelphia Police Department has begun making more traffic stop data public. The work of the Defenders Association of Philadelphia will ensure that available data are presented to the public accessibly, aiding policymakers, practitioners, and community members in the oversight of the Achieving Driving Equity Ordinance.

Empowering Change: The Role of Data in Transforming Policing Practices

Harnessing the power of data to scrutinize traffic stops is a pivotal step toward transparency, accountability, policy change, and equitable policing practices. Analysis of traffic stop data enables people to uncover patterns, identify potential biases, and initiate informed conversations about reform. As communities strive for a fair and just criminal legal system, ongoing efforts to collect, share, and analyze data will be crucial in reshaping law enforcement practices. Government agencies, advocates, and residents can use data-driven insights and corresponding legislation to ensure traffic stops are focused on traffic safety, rather than a source of disparities. As society moves forward, the commitment to using data as a catalyst for positive change remains a cornerstone in the collective pursuit of a more just and equitable society.