Balancing equity-based goals with market-driven forces in land development: The case of density bonusing in Toronto
Bibliographic record
Abstract
This article explores the connections between planning and land rent through a case study of density bonusing in Toronto, known as ‘Section 37’ – a form of land value capture. Density bonusing facilitates speculative bidding on future rents by private developers seeking ‘highest and best’ land uses – or efficient land uses – yet has implications related to equity when the unearned increment is extracted to recover value and invest in public goods. We situate land value capture within debates on the unearned income derived from land development in cities. We view the case of density bonusing through the lens of discretionary planning systems operating through flexible mechanisms. Specifically, we consider the direct role of planners towards balancing private interests with public goods in the face of shifting market and political contexts. The findings show that securing public goods from private land development through the unearned increment lacks consistency and predictability when the flexibility exercised by development actors drives planning decision-making. We conclude with a discussion on the implications for discretionary planning and land value capture in market-intensive, neoliberal environments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".