Assessing Municipal Lawn Care Reform: The Case of a Lawn Pesticide By-Law in the Town of Caledon, Ontario, Canada
Bibliographic record
Abstract
This paper explores the significance of the rapid increase in municipal by-laws restricting the use of pesticides on lawns and their support by the courts and higher political jurisdictions in Canada. Using a review on the literature of lawn management, recent policy events in Canada, and a case study of the Town of Caledon in Ontario, the study confirms the power of local democratic forces in support of such initiatives, but cautions against an overly positive view. Selective community backing, the continued endorsement of an industrial lawn aesthetic, and the continued strength of the pesticide industry sector and its supporters, can compromise both the extent and quality of the effectiveness of a by-law. The study points to the value and urgency of further research and assessments of individual municipal by-laws and their local and cumulative impacts.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.016 | 0.006 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".