- Browse/Search the Program
Search
Browse By Day
Browse By Time
Browse By Person
Browse By Mini-Conference
Browse By Division
Browse By Session or Event Type
Browse Sessions by Fields of Interest
Browse Papers by Fields of Interest
- Information Menu
Search Tips
Conference
Location
About APSA
- Navigation and Settings Menu
Personal Schedule
Change Preferences / Time Zone
Sign In
- Social Media Menu
Facebook
X (Twitter)
Better Models, Better Predictions
Sat, September 2, 10:00 to 11:30am PDT (10:00 to 11:30am PDT), Virtual, Virtual 14Session Submission Type: Created Panel
Session Description
Each paper develops innovative models to more effectively address persistent problems in political methodology, and where appropriate provides corrections for underappreciated biases.
Sub Unit
Chair
Discussant
Individual Presentations
A Descriptively Accurate Generative Model of US Congressional Elections - Daniel Ebanks, Harvard University; Jonathan N. Katz, Caltech; Gary King, Harvard University
Estimating Racial Disparities When Race Is Not Observed - Cory McCartan, Harvard University; Jacob Goldin; Daniel Ho, Stanford Law School; Kosuke Imai, Harvard University
A Gaussian Process Framework for Social Science Models - Yehu Chen, Washington University in St. Louis; Roman Garnett, Washington University in St. Louis; T. Ryan Johnson, Washington University in St. Louis; Jacob M. Montgomery, Washington University in St. Louis; Annamaria Prati, Washington University in St. Louis
Remote Control: Debiasing Remote Sensing Predictions for Causal Inference - Eliana Stone, Yale University; Luke Sanford, Yale University; Matthew Gordon
Detecting Political Sectarianism on Twitter Using Generative Language Models - Patrick Y. Wu, American University; Haohan Chen, The University of Hong Kong; Zhanna Terechshenko, New York University; Richard Bonneau, NYU; Jonathan Nagler, New York University; Joshua A. Tucker, New York University