Toronto's Housing Crisis: An Intersectional Politics of Housing and Settlement Services for Refugees
Bibliographic record
Abstract
In this dissertation, I unpack the intersectional politics of the housing crisis in Toronto through the perspectives of frontline staff working in non-profit organisations. Two critical questions frame this study. Firstly, how have service providers addressed the housing and settlement needs of refugees in the context of Canada’s housing crisis? Secondly, how are race, class, language and citizenship status tied into the politics of housing and settlement service provision in Toronto? Utilising semi-structured interviews with frontline staff employed in various non-profit across Toronto, this research identifies and analyses systemic barriers to housing access among newly arrived refugees in Canada as they cut across race, class, language and citizenship status. This study interrogates the disjuncture between immigration and housing policies, programs and procedures and access to rental housing among refugees in Toronto. I draw on antiracist feminist frameworks, particularly intersectionality and theories of home-making, to enrich current conceptualisations of housing access and inequality in Canada. I unpack barriers refugees face when accessing the private rental market in Toronto, to reveal the multilayered ways in which marginalized communities experience housing inequality in Canada. In doing so, this dissertation reveals the limitations of the reliance on private housing stock for housing refugees as they face barriers, including lack of Canadian references and credit scores, lack of employment, language barriers and housing discrimination. Additionally, this study underscores the limitations of settlement and housing service provision available to vulnerable populations, such as refugees in Toronto. By engaging with the voices of frontline staff who consistently interact with refugees, this study sheds light on the intersectional praxis of service provision and the limitations service providers confront when administering programs for vulnerable populations in Toronto. Finally, this study unveils the roles community and grassroots organisations, such as the Ontario Coalition Against Poverty, Association of Community Organizations for Reform Now, and Parkdale Organize!, play in (re)imagining housing justice in Toronto. This study identifies and contributes a novel methodological and conceptual approach to housing research in geography by bringing to the fore frontline staff as a key category of analysis seldom featured in studies on Canada’s housing system.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.036 | 0.023 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".