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Record W2012243919 · doi:10.1017/s0008423902778463

Institutional Experiments in the Restoration of the North American Great Lakes Environment

2002· article· en· W2012243919 on OpenAlexaffabout
Mark Sproule‐Jones

Bibliographic record

VenueCanadian Journal of Political Science · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicTransboundary Water Resource Management
Canadian institutionsMcMaster University
Fundersnot available
KeywordsBureaucracyInterdependenceIncentiveCommissionStakeholderEnvironmental planningPublic administrationProcess (computing)Conceptual frameworkBusinessPolitical scienceProcess managementEnvironmental resource managementPublic relationsGeographyComputer scienceEconomicsSociologyFinancePolitics

Abstract

fetched live from OpenAlex

The article reports the findings of a study of the 43 institutional arrangements in the most severely polluted bays, harbours, river mouths and connecting channels in the Great Lakes of North America. These arrangements were designed by the governments of Canada and the United States and their respective provinces and states, in order to formulate and implement Remedial Action Plans (RAPs) to restore impaired beneficial uses. The RAPs were conceived, adopted and monitored by the International Joint Commission. The theory of common property resources is used to develop a conceptual framework to assess the effectiveness of the RAPs. Success at the planning stages is associated with a representative and inclusive process of ''stakeholder'' agenda setting, and success at an implementation stage with a system of pooled interdependencies among implementing organizations. There are, however, competing incentives for the bureaucratic organizations that design RAPs, and evidence suggests that these can be more powerful than the RAP programme itself. The success of the RAPs is thus mixed.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.562
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.005
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.034
GPT teacher head0.263
Teacher spread0.229 · 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 teacher head, not a consensus.

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

Citations15
Published2002
Admission routes2
Has abstractyes

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