Some Progress In Policing Data

Berkeley Computational Social Science Forum

CSS Training Program

April 12, 2022
4:00pm to 5:00pm
Virtual Participation

Register

Berkeley Computational Social Science Forum
Date: Tuesday, April 12, 2022
Time: 4:00-5:00 PM Pacific Time
Location: Virtual Participation – Register to attend via Zoom

Some Progress In Policing Data

Jack Glaser, Professor, Goldman School of Public Policy, UC Berkeley
Abstract: In this talk, Professor Glaser will describe his experiences working to obtain and analyze data on police stops and use of force.  Scientific collaborations, grass-roots advocacy and projects, journalistic ventures, litigation, and government programs have all advanced the quantity, quality, and availability of policing data over the past two decades.  Data analytic innovations have overcome some of the shortcomings of the data.  Glaser will highlight how newly available data allow for tests of the effects of discretion on racial disparities in police searches.

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. 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. This Forum is organized as part of the Computational Social Science Training Program, and weekly meetings are hosted by researchers from BIDS and D-Lab. The group welcomes social scientists and 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. 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 or if you are interested in presenting current research for an upcoming session.

Speaker(s)

Jack Glaser

Professor, Goldman School of Public Policy

Jack Glaser is a social psychologist whose primary research interest is in stereotyping, prejudice, and discrimination. He studies these intergroup biases at multiple levels of analysis. For example, he investigates the unconscious operation of stereotypes and prejudice using computerized reaction time methods, and is investigating the implications of such subtle forms of bias in law enforcement. In particular, he is interested in racial profiling, especially as it relates to the psychology of stereotyping, and the self-fulfilling effects of such stereotype-based discrimination. Additionally, Professor Glaser has conducted research on a very extreme manifestation of intergroup bias - hate crime - and has carried out analyses of historical data as well as racist rhetoric on the Internet to challenge assumptions about economic predictors of intergroup violence. Professor Glaser is working with the Center for Policing Equity as one of the principal investigators on a National Science Foundation- and Google-funded project to build a National Justice Database of police stops and use of force incidents. He is the author of Suspect Race: Causes & Consequences of Racial Profiling.