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Record W2905823978 · doi:10.36646/mjlr.40.4.role

The Role of Local Governments in Great Lakes Environmental Governance: A Canadian Perspective

2007· article· en· W2905823978 on OpenAlexaffabout
Marcia Valiante

Bibliographic record

VenueUniversity of Michigan Journal of Law Reform · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicWater Resources and Governance
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsPerspective (graphical)Corporate governanceLaw reformEnvironmental governanceLocal governancePolitical scienceEnvironmental lawEnvironmental planningBusinessPublic administrationLocal governmentGeographyLaw

Abstract

fetched live from OpenAlex

Restoration of environmental integrity in the Great Lakes Basin has been only a qualified success after thirty-five years of efforts pursuant to policies developed by federal, state, and provincial governments. Many unresolved problems stem from activities under local government control, yet in the past local governments were excluded from Great Lakes policy-making. By looking at recent changes in the powers, interests, experience, and influence of local governments in Ontario, this Essay concludes that local governments now have the ability to participate meaningfully in Great Lakes policy formation and implementation. To include local governments would improve the chances of successful restoration of ecosystem integrity. However, a number of challenges must first be tackled so that an expanded role for local governments can be most effective.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.154
Threshold uncertainty score0.981

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0250.018
Scholarly communication0.0080.003
Open science0.0020.004
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.004
GPT teacher head0.188
Teacher spread0.184 · 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 designQualitative
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

Citations4
Published2007
Admission routes2
Has abstractyes

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