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Quantitative Study of Race & Gender
Fri, September 6, 4:00 to 5:30pm, Pennsylvania Convention Center (PCC), 109ASession Submission Type: Created Panel
Session Description
This panel explores questions in racial and gender politics from the perspective of political methodology, offering innovative quantitative approaches to study segregation, law enforcement practices, social interactions, and political discourse. Through cutting-edge applications of virtual reality and artificial intelligence, the presentations offer a rich array of novel techniques that complement and extend existing approaches to understanding the role of race and gender in politics and other social domains.
Sub Unit
Individual Presentations
Evaluating Measurement Error in Segregation: Algorithm-Assisted Bias Correction - Jacob Brown, Harvard University; Christopher Kenny, Harvard University; Tyler Simko, Harvard University
Simultaneous Sensitivity Analyses: An Application to Racial Bias in Policing - Thomas Leavitt, City University of New York (CUNY); Jacob Bowers, University of Illinois, Urbana-Champaign; Luke Miratrix
Measuring Racial Avoidance on Virtual Streets - Bryce Dietrich, Purdue University; Melissa Sands, London School of Economics
She Doesn’t Look Presidential: Analyzing Gendered Fashion in Politics - Samantha Register, University of Colorado Boulder; Katie Glenn, University of Colorado Boulder
The Visual Conjoint: A New Solution for Social Desirability Bias - Rachel Bernhard, Nuffield College