How is Public Housing These Days? Residualization, Financial Precarity, and Dilapidation in Toronto and Montréal’s Public Housing Sector (2007-2021)
Bibliographic record
Abstract
This paper hopes to fill in the literature and knowledge gap on recent conditions and trends within the public housing sector in Canada. To narrow the focus, two things were done. The public housing agencies of Toronto (Toronto Community Housing Corporation) and Montréal (Office municipal d’habitation de Montréal) were chosen as case studies. Then, a review literature review of recent publications was used to identify three major trends in the wider social housing sector: increasing residualization, financial precarity, and dilapidation. The research looks at how these agencies fit (or do not fit) these trends identified. Agency and municipal publications, interviews, and e-mail correspondences were utilized to spearhead conclusions. It was discovered that the TCHC and OMHM fit into these trends, although recent funding commitments have created change, at least in the short term. Various recommendations, from careful social mixing strategies to a dedicated municipal tax, were discussed as potential ways to address these issues. This research may help guide public and social housing policy and research for other jurisdictions, as well as in future region- and systems-wide reviews of public and social housing in Ontario and Québec.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.006 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".