Effectiveness of density bonusing in securing affordable housing: a study of Toronto downtown and waterfront area
Bibliographic record
Abstract
Today, Downtown and Central Waterfront area (the Area), through density bonusing/Section 37 agreements, has seen many condominium developments. In the situation of limited funding source available to municipalities, Toronto has used density bonusing as an effective incentive tool for securing the most needed community benefits from developers, in exchange for height/density beyond the prevailing by-laws. However, although the priority of density bonusing is to encourage/expand the growth of affordable housing in the City, due to some limitations to the tool, the extraction of affordable housing units from major condominium developments in the Area has been restricted. Based on literature review, a study of the City's data on projects approved for density bonusing in the Area, and a comparative study with Vancouver Downtown, this paper addresses several concerns about density bonusing. Finally, this paper puts forward a list of recommendations for the City to consider while dealing with the growing issues with the existing density bonusing policies for better inclusion of affordable housing in condominium developments in the Area.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".