Social housing stigma in Toronto: Identifying asymmetries between stereotypes and statistical actualities of health, crime, and human capital

Abstract

Research on social housing stigma has proliferated due to growing concern over the effects of territorial stigmatization. The stereotyping of social housing as a site of ill-health, criminality, and low human capital stems from empirically ambiguous narratives created and recirculated through popular modes (e.g., social media platforms, news coverage). This paper combines principal component analysis, k-means cluster analysis, and geographic information systems to create and visualize clusters denoting different levels of health, crime, human capital, and dwelling composition in the city of Toronto, Canada. The quantitative research design allows for the identification of “asymmetries,” which are census tracts or neighbourhoods assigned to clusters indicative of high social housing density, and one of either sound health, low crime, or high human capital. The results reveal a spatial patterning of asymmetries in the inner city West End and Downtown, and in inner suburban North York, Etobicoke, and Scarborough. Overall, the paper illustrates the need to assess the empirical foundations of social housing stereotypes. Critically assessing stereotypes is important as they belie the rationale for social housing residents' living situations; pathologizes their identity, behaviour, and home; and generates public support for neoliberal solutions that displace long-term residents from their communities.