Hello! My name is Semra Sevi. I am a Banting postdoctoral researcher at Columbia University, working with Donald Green.
Broadly speaking, I am interested in political representation, the role of age, gender and immigration in politics, voting behaviour, voting systems, and legislative politics.
Methodologically, my research leverages several quantitative approaches. I employ observational data, experiments, as well as causal inference designs. Before Columbia, I earned my PhD at the Université de Montréal and my Honours BA and MA from the University of Toronto.
My dissertation focuses on two areas: descriptive representation, and how voters evaluate female candidates for office. To address these questions, I built an original dataset detailing the district level data for all Canadian federal candidates from 1867-2019. This dataset includes unique id for each individual who ran for federal elections, riding names, province, date of birth for all elected MPs by year, gender, occupation, party names, switchers, vote shares and raw votes. Here is a full list of all the variables and a description for each. I also collected similar data for all candidates in the Ontario provincial elections also from 1867-2019. You can find both datasets here.
*If you are a first-generation student applying to political science Ph.D. programs or Canadian funded postdoctoral fellowships, I would be more than happy to discuss and give comments on your materials. I especially welcome applicants from underrepresented backgrounds.