Stimulating the rental market : federal and provincial housing policy from 1935-2019
Bibliographic record
Abstract
[Para. 1 of Introduction] The Canadian Rental Housing Index outlines that in 2018, Ontario’s rental market is as unhealthy as it has ever been (Canadian Rental Housing Index, n.d.). This is due to the fact that the supply of rental housing has not kept up with the growing demand for this tenure type. From 2011-2016, the average rate of renter formation1 was approximately 34,000 renter households per year (Urbanation, 2019). During this same period approximately 5,000 purpose-built rental units were completed CMHC, 2018). This misalignment between the supply and demand of rental housing has resulted in extremely low vacancy rates. In 2017, the vacancy rate in Ontario hit 1.6%, the lowest it has been since 2000 (CMHC, 2017). It is important to recognize that the roots of this problem in Ontario reach back further than the last ten years, but the problems have become increasingly acute during this time frame.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".