This course focuses on leveraging administrative data for bias audits, specifically assessing disparate coverage with mobility data for COVID-19 policy. The learning outcomes include understanding how to conduct bias audits using administrative data and analyzing disparate coverage with mobility data. The course teaches skills such as identifying confounding variables and drawing conclusions from the analysis. The teaching method involves presenting research findings in the areas of bias audits and data analysis. This course is intended for researchers, policymakers, and data analysts interested in using administrative data for assessing biases in policy implementation.
Leveraging Administrative Data for Bias Audits - Assessing Disparate Coverage with Mobility Data for COVID-19 Policy
Association for Computing Machinery (ACM) via YouTube
Overview
Syllabus
Introduction
Background
Confounding
Analysis
Conclusion
Taught by
ACM FAccT Conference