Georgy Tarasenko

Ph.D. Candidate in Government

Cornell University

I am a Ph.D. Candidate in Government at Cornell University studying the micro-foundations of political dissent, obedience, and preference falsification across democratic and authoritarian contexts. My dissertation, Dissent: A Behavioral Political Economy Approach to Contesting Authority, examines why individuals resist, comply with, or conceal their preferences under political authority.

My research combines laboratory and survey experiments, formal models, causal inference, and computational text- and audio-as-data. Substantively, I work on authoritarian politics, democratic backsliding, public opinion under repression, political psychology, and behavioral political economy.

At Cornell, I am a graduate fellow at the Institute for European Studies and the Center on Global Democracy, an affiliate of the Cornell Center for Social Sciences, and a research assistant for the Russian Election Study.

research

My research brings together comparative politics, political economy, and behavioral sciences, while being deeply informed by political theory and intellectual history. In my dissertation book project, I plan to examine the comparative behavioral political economy of dissent. More specifically, I am intended to investigate the psychological mechanisms that drive individuals to resist autocrats, illiberal leaders, and democratic backsliding—and how these mechanisms interact with institutions, culture, and historical legacies. Beyond this core agenda, I maintain broader interests in questions in political psychology, behavior, and the political economy of development. I am also engaged with metascientific questions related to research replicability and knowledge cumulation in social sciences.

Methodologically, I primarily employ quantitative and computational approaches, while integrating qualitative insights when appropriate. My work is driven by substantive questions rather than methodological allegiance, but I have particular interests in survey methodology (e.g., preference elicitation on sensitive topics, multimodal data analysis including text, audio, and behavioral traces), and in the sensitivity of small-area estimation techniques to site selection. I also think on broader problems in causal inference and experimental design, including issues related to site selection, factorial and adaptive experiments and other general questions in econometrics, psychometrics, GIS, and machine learning.

bio