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The proposed research project aims to understand to what extent Canadian neighbourhoods vary based on the accessibility of transportation and identify which socially disadvantaged groups of people are most impacted by limited access to transport. The interns will analyze a large dataset released by “Infrastructure Canada and Statistics Canada” which measures how easy it is for people to reach important places like schools, workplaces, grocery stores, healthcare facilities. They will also incorporate sociodemographic data from the Canadian Census. The research will be carried out using data analysis, machine learning, and geographic information systems. The expected outcomes of this project include a developed typology of neighbourhoods based on the accessibility to important destinations, a better understanding of transportation challenges faced by different equity-deserving groups, and suggestions to improve the dataset. The research will benefit policymakers, transportation providers, and communities across Canada.
Steven Farber
National University of Kyiv-Mohyla Academy
Sociology
Transportation (excluding aerospace); Public Service, Policy, and Governance
University of Toronto
Globalink Research Award
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