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Record W3021493680

The Power of Prevention: The extent of Environmental Authority in the Context of Local Government

2019· article· en· W3021493680 on OpenAlexaboutno aff
Colleen Thrasher, Jeremy Power

Bibliographic record

VenueeYLS (Yale Law School) · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Issues in South Africa
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Power (physics)Government (linguistics)Local governmentSociologyLocal authorityPolitical sciencePublic administrationGeographyLinguisticsArchaeologyPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

This article attempts to delineate the scope of a municipality’s legal power within the realm of environmental management. Part one of this article looks at the legal position of a municipal government in the Canadian constitutional framework. The authors note that municipalities are creatures of statute and their available powers are tightly prescribed by legislation. Part two of this article is a case study of the City of Toronto's efforts to manage pollution in the Great Lake region, particularly with respect to Lake Ontario. Despite the limits to a municipality’s power, the authors argue that many effective pollution prevention strategies fall within existing municipal authority. The authors conclude that a municipality has the unique and powerful ability to adopt effective source-control bylaws being the source of a significant amount of pollution.

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)0.012
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.050
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0130.078
Scholarly communication0.0130.010
Open science0.0020.010
Research integrity0.0030.004
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 head0.011
GPT teacher head0.267
Teacher spread0.256 · 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 designNot applicable
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

Citations1
Published2019
Admission routes1
Has abstractyes

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