Rental Housing Trends in Toronto: Should Conversions of Rental Buildings to Condominiums be Prevented?
Bibliographic record
Abstract
This report is focussed on the planning and housing policy problem of the loss of purpose-built rental housing in Toronto. Not only are very few units being built, but there has been an absolute decline in the city’s stock of purpose-built rental housing. The 957 purpose-built rental apartments at Lascelles Blvd. are part of a private sector share of 257,000 such units in the city. Planning in the public interest ought to improve conditions for all residents where possible and avoid doing harm. Planning decisions must not make a bad situation worse. Losing the 957 Lascelles Blvd. purpose-built (primary sector) rental apartments, together with any further losses that might result in the primary sector from such a precedent, will, for the reasons explained in this report, harm the interests of all renter households in the city. Supply will decrease, while need and demand continue to grow. This policy issue is about the City of Toronto’s purpose-built rental stock – the primary rental sector units. Few are being built now. Under current conditions in Toronto’s rental sector, it is premature, and it is not in the public interest, to lose more of this primary stock of rental housing. Research provided in this report documents: (1) the growing income gap between owners and renters; how Toronto’s rental housing does not “down-filter”; that rental-only zoning was abolished in the late 1960s; and that there has been a thirty-year trend of housing tenure segregation in Toronto.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".