Kirill Chmel

I am a first-year graduate student in Political Science at Columbia University. Previously I was a research fellow at the Ronald F. Inglehart Laboratory for Comparative Social Research and a lecturer at HSE University and University of London. I also worked as a research assistant for Indiana University and United Arab Emirates University.

I am generally interested in inequality and social policy. In my dissertation research I study how exposure to inequality in real life and on social media affects preferences for redistribution and support for an incumbent. As a scholar of autocratic politics, I am especially interested in how autocrats utilize economic segregation and redistribution for political ends.

Causal inference, bayesian statistics, and the application of machine learning algorithms to political research are some of my methodological interests. I also have a first-hand experience of working with surveys and different types of experiments. My GitHub repository contains the data I collected with my co-authors.

I was born in Samara, Russia. I moved to Moscow, Russia, in 2014 to pursue my BA in Political Science and MA in Applied Politics degrees from HSE University.

Download the latest version of my CV here and reach me at kc3580@columbia.edu.

selected publications

PLoS ONE

The Effect of Risk Framing on Support for Restrictive Government Policy Regarding the COVID-19 Outbreak

Kirill Chmel, Aigul Klimova, and Nikita Savin

2021

Abs

This confirmatory research investigates the influence of risk framing of COVID-19 on support for restrictive government policy based on two web survey experiments in Russia. Using 2x2 factorial design, we estimated two main effects–factors of risk severity (low vs. high) and object at risk (individual losses vs. losses to others). First, focusing on higher risks had a positive effect on support for the government’s restrictive policy. Second, focusing on the losses for others did not produce stronger support for the restrictive policy compared to focusing on personal losses. However, we found a positive moderation effect of such prosocial values as universalism and benevolence. We found that those with prosocial values had a stronger positive effect in the “losses for others” condition and were more willing to support government restrictive policy when others were included. The effects found in our experimental study reveal both positive and negative aspects in risk communication during the pandemic, which may have a great and long-term impact on trust, attitudes, and behavior.