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Record W316419269 · doi:10.5070/g312510696

Assessing Municipal Lawn Care Reform: The Case of a Lawn Pesticide By-Law in the Town of Caledon, Ontario, Canada

2007· article· en· W316419269 on OpenAlexaboutno aff
Clarine Lee-Macaraig, Linda Sandberg

Bibliographic record

VenueElectronic Green Journal · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect and Pesticide Research
Canadian institutionsnot available
Fundersnot available
KeywordsLawnCompromiseDemocracyPoliticsValue (mathematics)Public administrationLawPolitical scienceEcology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.230
Threshold uncertainty score0.893

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.005
Science and technology studies0.0160.006
Scholarly communication0.0060.001
Open science0.0030.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.020
GPT teacher head0.274
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2007
Admission routes1
Has abstractyes

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