Court Decisions, NIMBY Claims, and the Siting of Unwanted Facilities: Policy Frames and the Impact of Judicialization in Locating a Landfill for Toronto's Solid Waste
Bibliographic record
Abstract
This article examines the use of litigation by political actors to contest unwanted environmental policy options on the basis of NIMBY claims. It analyzes the discursive frames employed by policy actors to explain how one community in Northern Ontario could reject a facility to receive Toronto's waste while another in Michigan could not. The article employs a case study approach to trace the process of judicial and tribunal decisions about these two potential landfill sites. The research found that the judicial policy frames can serve as a determinative of outcomes of siting decisions in subsequent institutional settings and that such precedents could be overcome only when opponents reframed the issues to align with the interests of all parties. The article concludes that the specific characteristics of each institutional setting in which policy disputes take place are an important factor to explaining policy change or stability.
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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 | 0.018 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.025 | 0.043 |
| Scholarly communication | 0.016 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".