Land-use regulation and housing affordability: characterizing the impacts of restrictive zoning on Toronto's housing market through a case study of Ward 8 neighbourhoods
Bibliographic record
Abstract
Toronto’s housing affordability crisis continues to escalate. Increasing demand and land supply constraints prevent the housing and land market from reaching equilibrium, resulting in skyrocketing house prices and a disproportionately small number of additional units built. Despite efforts from City Council to increase affordable housing options, housing affordability concerns have yet to be adequately addressed. By collecting and analysing the market, zoning, and minor variance/consent data in Toronto’s Ward 8 neighbourhoods, this MRP argues that much of Toronto’s inner-suburban neighbourhoods contain overly restrictive land-use regulations that may worsen housing affordability and perpetuate suboptimal land values. The most restrictive areas and neighbourhoods appear to be experiencing the greatest effects of supply constraining regulations, as they have the highest growth in house prices, the greatest increase in housing services per unit upon rebuild, and disproportionately low per-square-foot property values in comparison to its sale price. This MRP also finds that community and institutional support for new development in Toronto’s neighbourhoods are contingent on conformity with existing physical neighbourhood character, whose definition favours the detached home. To help ease the housing affordability crisis, it is recommended that Toronto encourage a range and mix of housing typologies by removing policies and regulations that reinforce single-family only neighbourhoods
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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 | 0.002 |
| 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) | 0.002 | 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".