Computational Social Science Forum — Outercity Policing: Drivers of Police Spending in a Changing Metropolis

CSS Training Program

March 1, 2021
12:00pm to 1:30pm
Virtual Participation

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Computational Social Science Forum
Date: Monday, March 1, 2021
Time: 12:00-1:30 PM Pacific Time
Location: Register to receive the schedule and access links.

Outercity Policing: Drivers of Police Spending in a Changing Metropolis

Speaker: Ángel Ross, BIDS CSSTP Fellow; PhD Student in Sociology, UC Berkeley
Abstract: I explore the intersection of two major trends in the last forty years: a substantial investment in local law enforcement and the suburbanization of poor people, people of color, and immigrants. Studies consistently show that racial threat is an important predictor of municipal spending on police but nearly all analyses focus on the U.S.'s largest central cities. Drawing on a newly assembled panel dataset of approximately 200 cities in California between 2000 and 2018, I find that the determinants of police spending vary in the suburban periphery compared with the coastal urban core. Fixed-effects models that control for unobserved heterogeneity across cities suggest that suburbs with growing shares of both Black residents and renters spend more on police. Elaborating on the concept of renter threat, I show how increases in renter households and renter segregation in particular are associated with increases in police expenditures across a range of model specifications in suburbia but not among cities in the coastal urban core. The results underscore the importance of research on small- and medium-sized cities and suburbs not only because the majority of every major race/ethnic group now lives in suburbia, but also because the drivers of police spending vary across the metropolis in significant ways.

The Computational Social Science Forum is an informal setting for the interdisciplinary exchange of ideas and scholarship at the intersection of social science and data science. Weekly meetings are hosted by researchers from BIDS and D-Lab, and participants engage in a variety of activities such as presentations of work in progress, discussions and critiques of recent papers, introductions to new tools and methods, discussions around ethics, fairness, inequality, and responsible conduct of research, as well as professional development. We welcome social scientists researchers with interests in data science methods and tools, and data scientists with applications or interests in public policy, social, behavioral, and health sciences. Participants include graduate students, postdocs, staff, and faculty, and members are encouraged to attend regularly in order to foster community around improving computational social science research, supporting the development and research of group members, and fostering new collaborations. This Forum is organized as part of the Computational Social Science Training Program, and interested UC Berkeley community members are invited to use this registration form to receive the schedule and access links. Please contact css-t32@berkeley.edu for more information.

Speaker(s)

Ángel Mendiola Ross

PhD Student, Sociology, UC Berkeley

Ángel Ross is currently a PhD student in sociology with a designated emphasis in Global Metropolitan Studies. He conducts research at the intersection of (sub)urban sociology, race and inequality, housing, and policing. Their current project empirically tests evidence of racial threat and renter threat in California suburbs with a focus on communities on the receiving end of gentrification and displacement from the coastal urban core. Before pursuing a PhD, they received a Master of City Planning from the College of Environmental Design at UC Berkeley and BAs in sociology and economics from the University of Southern California. They previously worked as a senior research associate at PolicyLink based in Oakland, California. In his spare time before COVID-19, Ángel enjoyed playing drums with a rockabilly/soul band and a queer electronic group.