Research
In general, I’m deeply interested in measuring political attitudes and opinions primarily using dimensional scaling and machine learning. Furthermore, I have an ongoing research project with Jack Rametta on incorporating machine learning into experimental analyses in the social sciences. So far, my previous research has worked to better understand COVID attitudes and behaviors and the dimensionality of affective polarization.
Publications
- Populism and the affective partisan space in nine European publics: Evidence from a cross-national survey
- With Will Horne, James Adams, & Noam Gidron
- Assessing the effectiveness of COVID-19 vaccine lotteries: A cross-state synthetic control methods approach
- With Sara Kazemian, Carlos Algara, & Daniel J. Simmons
- The role of race and scientific trust on support for COVID-19 social distancing measures in the United States
- With Sara Kazemian & Carlos Algara
- The Interactive Effects of Scientific Knowledge and Gender on COVID‐19 Social Distancing Compliance
- With Carlos Algara, Christopher D. Hare, & Sara Kazemian
- The Conditional Effects of Scientific Knowledge & Gender on Support for COVID-19 Government Containment Policies in a Partisan America
- With Carlos Algara & Christopher D. Hare
Research in Preparation
Research Under Review
- Balance Tests Are Dead, Long Live Balance Tests: A New Machine Learning Approach to Detecting Randomization Failures (AJPS)
- With Jack T. Rametta
- Affect or Ideology?: The Heterogeneous Effects of Political Cues on Policy Support (AJPS)
- With Nicolás de la Cerda & Jack T. Rametta
Working Papers
- Towards a General Methodology of Bridging Ideological Spaces
- With Tzu-Ping Liu & Gento Kato
- Progressives and Never-Trumpers: Contrastive Principal Component Analysis as an Alternative Method for Public Opinion Research
- With Tzu-Ping Liu
- Rational Voting in the Age of Ideological Polarization & Responsible Parties: Examining Presidential Elections from 1972–2020
- With Carlos Algara