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Chapter 4. Observations On Compliance And Enforcement And Regional Fisheries Institutions: Overcoming The Limitations Of The Law Of The Sea

2011· book-chapter· en· W2270614722 on OpenAlexaboutno aff
Moira L. McConnell

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicWildlife Conservation and Criminology Analyses
Canadian institutionsnot available
Fundersnot available
KeywordsCommissionFisheries managementFisheries lawFisheryEnforcementFisheries scienceUnited Nations Convention on the Law of the SeaMarine fisheriesPoliticsGeographyPolitical scienceBusinessInternational lawFish <Actinopterygii>LawFishingBiology

Abstract

fetched live from OpenAlex

The Pacific Salmon Commission (PSC) is a somewhat unique bilateral fisheries management organization which in many ways is a reflection of the particular biology of the salmon species, the political geography of the Pacific Northwest of North America, and the complexity of fisheries relations between Canada and the United States in that area. This chapter describes the structure and operation of the Commission as a regional fisheries management organization (RFMO), the problems it has faced, and how they have been resolved. It suggests some reasons for the current period of success of the PSC and considers what lessons may be drawn for other RFMOs about sustainable fisheries management. Pacific salmon has been on the agenda of Canada and the United States for over 100 years. Keywords:Pacific Salmon commission (PSC); regional fisheries management organization (RFMO)

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)0.001
metaresearch head score (Gemma)0.001
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 score0.031
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.004
Scholarly communication0.0030.003
Open science0.0000.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0110.001

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 head0.406
GPT teacher head0.275
Teacher spread0.130 · 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

Citations2
Published2011
Admission routes1
Has abstractyes

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