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enforcement, specifically for the City of Los Angeles. To deepen the case for the City of Los
Angeles, the consultant team conducted quantitative and qualitative analyses on traffic
enforcement using data from LAPD and with Angelenos.
The consultant team also worked with LADOT and LAPD to identify relevant case studies for
further research through expert interviews. Some case study locations were identified based on
the degree or extent of the changes in traffic enforcement, while others were identified based on
likeness or proximity to the City of Los Angeles. Three case study locations were initially
selected as case studies (See Appendix F) for further exploration, including New Zealand;
Philadelphia, Pennsylvania; and Fayetteville, North Carolina
. Ultimately, a few other cities were
included in the expert interviews, including Berkeley, California and Oakland, California.
Additional details about the expert interviews are described in Section IV.D.
B. QUANTITATIVE DATA FINDINGS
The quantitative analysis focused on a descriptive analysis of California Racial and Identity
Profiling Act (RIPA) data. LAPD and LADOT provided additional data for the quantitative
analysis. These data are largely similar to public information from the RIPA data portal but also
include location information.
1. Purpose
Racial differences in policing and traffic stops are well documented.
36,37,38,39
The Traffic
Enforcement Study problem statement describes how police traffic enforcement
disproportionately affects people of color and the need to address disparities in traffic safety.
Documenting trends in Los Angeles was a critical grounding component of this study, even with
this background of empirical evidence from national trends. Therefore, the consultant team
analyzed the recent trends, spatial patterns, and racial/ethnic dimensions of LAPD traffic stops
as a critical component of the Traffic Enforcement Study.
This analysis answers the following questions from the data:
36
Pierson, E., Simoiu, C., Overgoor, J., Corbett-Davies, S., Jenson, D., Shoemaker, A., Ramachandran,
V., Barghouty, P., Phillips, C., Shroff, R., & Goel, S. (2020). A large-scale analysis of racial
disparities in police stops across the United States. Nature Human Behaviour, 4(7), Article 7.
https://doi.org/10.1038/s41562-020-0858-1
37
Roach, K., Baumgartner, F. R., Christiani, L., Epp, D. A., & Shoub, K. (2022). At the intersection: Race,
gender, and discretion in police traffic stop outcomes. Journal of Race, Ethnicity, and Politics, 7(2),
239–261. https://doi.org/10.1017/rep.2020.35
38
Cai, W., Gaebler, J., Kaashoek, J., Pinals, L., Madden, S., & Goel, S. (2022). Measuring racial and
ethnic disparities in traffic enforcement with large-scale telematics data. PNAS Nexus, 1(4),
pgac144. https://doi.org/10.1093/pnasnexus/pgac144
39
Knowles, J., Persico, N., & Todd, P. (2001). Racial Bias in Motor Vehicle Searches: Theory and
Evidence. Journal of Political Economy, 109(1), 203–229. https://doi.org/10.1086/318603