Professor Semra Sevi | How Big Data is Uncovering the Secrets of Canadian Elections

Apr 10, 2025 | behavioural sciences

About this episode

A key challenge in studying democracy is understanding who runs for office and what factors influence their success, particularly when it comes to descriptive representation – the extent to which a legislature reflects the demographic makeup of the population. Until recently, however, researchers had limited data on Canadian political candidates. Professor Semra Sevi of the University of Toronto has created the largest dataset of its kind, documenting every candidate who ran in Canadian federal and Ontario provincial elections since 1867. This comprehensive dataset has already enabled several groundbreaking studies on Canadian democracy. Read More

Original Article Reference

Summary of the articles: ‘Who Runs? Canadian Federal and Ontario Provincial Candidates from 1867 to 2019’, doi.org/10.1017/S0008423920001213; ‘Do Women Get Fewer Votes? No’, doi.org/10.1017/S0008423918000495; and ‘Is Incumbency Advantage Gendered?’, doi.org/10.1111/lsq.12376

Contact

For further information, you can connect with Professor Semra Sevi at semra.sevi@utoronto.ca

W: https://www.politics.utoronto.ca/people/directories/all-faculty/semra-sevi

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