Computational Social Science Forum
Date: Monday, April 19, 2021
Time: 12:00-1:30 PM Pacific Time
Location: Register to receive the schedule and access links.
Speaker: Alissa Skog, Senior Research Associate with the California Policy Lab at UC Berkeley
Moving Beyond the Model: Pretrial Risk Assessments in Practice
Abstract: The Public Safety Assessment (PSA) is an empirically-based risk assessment tool that is used to inform pretrial release decisions across the country. The tool measures the risk of failing to appear at a court hearing, an arrest for new criminal activity while on pretrial release, or arrest for new violent criminal activity while on pretrial release. San Francisco adopted the PSA in May 2016. In addition to the tool, criminal justice stakeholders in the county developed a local policy document - known as the Decision-Making Framework (DMF) - to guide releases. The San Francisco DMF includes a number of charge-based overrides to the tool that increase the recommended supervision level or automatically generate a recommendation not to release.
The California Policy Lab (CPL) is validating the implementation of the PSA in San Francisco to examine the accuracy and reliability of the PSA in predicting failures to appear, new arrests, and new arrests for violent offenses for persons released pretrial in San Francisco as required by California Senate Bill 36. We also measure whether there is any disparate effect or bias based on sex or race/ethnicity. Lastly, we assess how the addition of the DMF impacts the predictive validity of the PSA overall and by different sex or race/ethnicity.
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 firstname.lastname@example.org for more information.