Le paysage en tant que savoir : capitalisme racial, science citoyenne et approches statistiques de la modélisation environnementale
Avec Dillon Mahmoudi (University of Maryland, Baltimore County)
Horaire : mardi 15 octobre 2024, 12h30 à 13h30
Salle : 2109 A-B (385, rue Sherbrooke Est, Montréal, QC)
Zoom : https://INRS.zoom.us/j/6325939377
Note : La présentation aura lieu en anglais. Les questions pourront être posées en français.
Description
L’atelier prendra la forme d’une communication de 35 minutes suivie d’une période d’échange. La série d’Ateliers-midi quantitatifs vise à dynamiser la communauté de chercheuses et chercheurs québécois en sciences sociales mobilisant des méthodes quantitatives. Étudiant.e.s et professeur.e.s sont invité.e.s à y participer et soumettre des propositions de présentation.
Bio (Eng)
Dillon Mahmoudi is an Associate Professor of Geography and Environmental Systems at UMBC, specializing in urban, digital, and economic geography. His research focuses on the intersections of cities, technology, political ecology, and uneven development, particularly around race, class, and environmental inequality. His current work involves combining geo-statistical methods with co-created, community-based initiatives aimed at addressing socio-environmental injustices. He holds a BS in Computer Science from Georgia Tech and a Ph.D. in Urban Studies from Portland State. He also directs the Just Maps GIS Masters program and is a Faculty Fellow at the Hilltop Institute.
Résumé (Eng)
Citizen science plays a crucial role in filling the gaps left by the state in environmental monitoring. This study examines how low-cost sensors deployed by residents—such as air quality monitors, rain gauges, and biodiversity apps—can complement national services and research projects by providing more granular, localized data. However, participation is unevenly distributed across geographies, shaped by processes of racial capitalism, leading to a pattern of socio-ecological segregation. Higher-income, predominantly white neighborhoods are more likely to engage in these citizen science projects, while low-income and BIPOC (Black, Indigenous, and People of Color) communities are underrepresented. This presentation applies a zero-inflated hurdle model to account for missing data and explore the socio-ecological disparities that emerge from uneven participation. By highlighting gaps in data representation and early warning systems, the statistical analysis, grounded in critical theory, reveals how these inequalities perpetuate environmental injustices and reinforce feedback loops that entrench uneven socio-ecological spaces. The presentation concludes by discussing the future of citizen science, with a focus on addressing inequities and preventing the entrenchment of spatial disparities in large government-based and private environmental models.