Advocacy Coalitions in Ontario Land Use Policy Development
Bibliographic record
Abstract
Abstract In 2005, the Ontario government passed the Places to Grow Act and the Greenbelt Act, both major changes in land use policy designed to preserve greenspaces and combat urban sprawl in the Greater Golden Horseshoe, Canada's largest conurbation. This article examines the actors, actor beliefs, and inter‐actor alliances in the southern Ontario land use policy subsystem from the perspective of the Advocacy Coalition Framework (ACF). Specifically, this paper undertakes an empirical examination of the ACF's Belief Homophily Hypothesis, which holds that inter‐actor alliances form on the basis of shared policy‐relevant beliefs, creating advocacy coalitions. The analysis finds strong evidence of three advocacy coalitions in the policy subsystem—an agricultural coalition, an environmentalist coalition, and a developers' coalition—as predicted by the hypothesis. However, it also finds equally strong evidence of a cross‐coalition coordination network of peak organizations, something not predicted by the Belief Homophily Hypothesis, and in need of explanation within the ACF.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".