Real estate developers’ influence of land use legislation in the Toronto region: An institutionalist investigation of developers, land conflict and property law
Bibliographic record
Abstract
This paper investigates the role of real estate developers in shaping land use legislation, land use planning and property law. The conceptual framework draws on third-phase institutionalism and socio-legal theory to examine actors and ideas that influence knowledge and practices of land use, planning and property. This paper confronts absences in planning theory that overlook the role of real estate developers in disputes over land, especially their role in shaping the legislative framework governing land use. The argument is that property law is not simply an objective system of rules interpreted by lawyers, judges and the courts. Neither is it a singular concept protecting private property rights. Rather, it is a complex concept and institution that emerges in practice through political processes, such as social movements, the exercise of power and influence by elite actors, and strategic acts by political actors navigating diverse and competing agendas. The empirical evidence informing this argument derives from case study research of land conflicts on the Oak Ridges Moraine in the Toronto region, Canada, with particular attention given to the relationship between real estate developers, social movement actors, and politicians involved in resolving the conflict.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.004 | 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".