Predicting neighbourhood change using big data and machine learning: Implications for theory, methods, and practice – University of Sydney Symposium, 10-11 August 2020
Despite decades of research on neighborhood change, there has been little corresponding methodological development: studies still tend to either rely primarily on demographic data aggregated at the neighborhood level (which masks complex and micro-scale causal dynamics), or on in-depth case studies (which present challenges for generalization). Advances in data science, particularly if informed by critical …