Environmental Roots of Urban Inequality
My primary research investigates the formation and development of racial-environmental inequality in cities, linking spatial, quantitative, and computational and machine learning methods to produce novel longitudinal data. This research is enabled by historical data extraction using a variety of computational methods (see this article on machine learning approaches to analyzing archival data, as well as this chapter on ML methods and large-scale data in urban research). I use these original data to conduct the first comparative analysis of urban environmental inequality in the late 19th and early 20th centuries, finding that the racialization of environmental inequality emerged alongside and in relation to the initial formation of segregated and unequal neighborhoods (see this article in Social Forces, as well as this article in Socius). This research further suggests new directions to embed urban sociology within a social-environmental perspective.
Supported by the SEEKCommons Project (National Science Foundation FAIROS RCN Award 2226425).
Related publications
- Tollefson, J. 2026. “Environment and the racialization of space in US cities.” Social Forces (online first).
- Candipan, J. and Tollefson, J. 2024. “Machine learning and large-scale data for understanding urban inequality.” The Oxford Handbook of the Sociology of Machine Learning, edited by C. Borch and J.P. Pardo-Guerra. Oxford, UK: Oxford University Press.
- Frickel, S. and Tollefson, J. 2022. “When environmental inequality racialized: Historical evidence from Providence, Rhode Island.” Socius 8:1-14.
- Tollefson, J., Frickel, S. and Restrepo, MI. 2021. “Feature extraction and machine learning techniques for identifying historic urban environmental hazards.” PLoS ONE 16(8): e0255507.
- Tollefson, J. and Frickel, S. 2021. “Gasworks, lost and found.” Urban Omnibus. New York: Architectural League of New York. July 1.