Costs and Consequences of Traffic Fines and Fees: A Case Study of Open Warrants in Las Vegas, Nevada

Traffic stops and tickets often have far-reaching consequences for poor and marginalized communities, yet resulting fines and fees increasingly fund local court systems. This paper critically explores who bears the brunt of traffic fines and fees in Nevada, historically one of the fastest growing and increasingly diverse states in the nation, and one of thirteen US states to prosecute minor traffic violations as criminal misdemeanors rather than civil infractions. Drawing on legislative histories, we find that state legislators in Nevada increased fines and fees to raise revenues. Using descriptive statistics to analyze the 2012–2020 open arrest warrants extracted from the Las Vegas Municipal Court, we find that 58.6% of all open warrants are from failure to pay tickets owing to administrative-related offenses—vehicle registration and maintenance, no license or plates, or no insurance. Those issued warrants for failure to pay are disproportionately for people who are Black and from the poorest areas in the region. Ultimately, the Nevada system of monetary traffic sanctions criminalizes poverty and reinforces racial disparities.

May I Talk to You for a Minute? An Assessment of Street Stops and Officer Decision-Making

The overwhelming majority of research on officer-initiated contacts with civilians is drawn from traffic stops, while relatively little is known about officer decision-making during non-vehicular, street stops. The current study fills this gap by examining intrusive detentions, investigatory actions and enforcement activities undertaken by the police during street stops. Using data from a racially/ethnic diverse metropolitan area, analyses examine encounter-related variables, civilian and officer-related demographic characteristics, and contextual correlates of actions undertaken during these incidents. Conclusions drawn from this study provide specific insight into the patterns and practices of street stop encounters and offer a contribution to our broader understanding of police-civilian encounters.

Racial demographics explain the link between racial disparities in traffic stops and county-level racial attitudes

Disparities in the treatment of Black and White Americans in police stops are pernicious and widespread. We examine racial disparities in police traffic stops by leveraging data on traffic stops from hundreds of U.S. counties from the Stanford Open Policing Project and corresponding county-level data on implicit and explicit racial attitudes from the Project Implicit research website. We find that Black-White traffic stop disparities are associated with county-level implicit and explicit racial attitudes and that this association is attributable to racial demographics: counties with a higher proportion of White residents had larger racial disparities in police traffic stops. We also examined racial disparities in several post-stop outcomes (e.g., arrest rates) and found that they were not systematically related to racial attitudes, despite evidence of disparities. These findings indicate that racial disparities in counties’ traffic stops are reliably linked to counties’ racial attitudes and demographic compositions.

Racial bias in police traffic stops: White residents' county-level prejudice and stereotypes are related to disproportionate stopping of Black drivers

Racial disparities in policing are well documented, but the reasons for such disparities are often debated. The current research weighs in on this debate using a regional-level bias framework: We investigate the link between racial disparities in police traffic stops and regional-level racial bias, employing data from over 130 million police traffic stops in 1,413 US counties and county-level measures of racial bias from over 2 million online participants. Compared to county demographics, Black drivers were stopped at disproportionate rates in the majority of counties. Crucially, disproportionate stopping of Black drivers was higher in counties with higher levels of racial prejudice by White residents (rs = 0.07 -0.36). Furthermore, county-level aggregates of Whites’ threat-related stereotypes were less consistent in predicting disproportionate stopping (rs = 0.00 -0.19). These observed relationships between regional-level bias and racial disparities in policing highlight the importance of context in which police operate.

Disrupting the Traffic Stop–to-Deportation Pipeline: The New York State Greenlight Law’s Intent and Implementation

This article analyzes the traffic stop–to-deportation pipeline in New York State, how it harms children of immigrants, and how New York’s Greenlight Law seeks to disrupt it but has been hobbled by an implementation gap. It first establishes the phenomenon of the traffic stop–to-deportation pipeline by documenting how traffic stops are a key cause of deportations in New York State. Second, it analyzes how the pipeline harms (mostly US citizen) children of undocumented immigrants in New York State, who are more than 7 percent (more than 300,000) of New York State’s children. The pipeline makes these children fear and mistrust the police; harms their educational, social, and brain development; and consumes family income with the Mexican driver tax (costs incurred because parents could not get a driver’s license). Third, the article analyzes how the Greenlight Law should help remedy these harms, and how an implementation gap leaves many parents and children vulnerable to the pipeline. The implementation gap is partly due to the pandemic, but also driven by political and other factors that could be addressed by policy. Finally, the article analyzes how variation in implementing the Greenlight Law could leave the pipeline undisrupted and lead to unequal protection of the law by place in New York State. The article makes policy recommendations for stronger enactment to reduce the pipeline’s harms.

Racial characteristics of areas and police decisions to arrest in traffic stops: multilevel analysis of contextual racial effects

PurposeThe present study assesses the contextual racial effects on police decisions to arrest in traffic stops.Design/methodology/approachA hierarchical logistic regression model is conducted using data collected from the Houston Police Department and US census.FindingsThe authors’ multilevel analysis indicates that the racial effect on police decision to arrest is more likely to be contextual than individual. Black and Hispanic drivers have no significant difference from White drivers in police decisions to arrest when area variations are controlled. In contrast, the concentrations of Blacks and other racial minorities in areas are significantly associated with the chance of being arrested by police in traffic stops. However, as the level of racial diversity increases in an area, the chance of being arrested is likely to decrease.Originality/valueThis study demonstrates the importance of racial characteristics of areas in the study of racial profiling and related police practice.