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Record W4406090814 · doi:10.1139/cjfas-2024-0271

Contract and sustain: evaluating the results of progressive implementation of limited entry and catch shares in West Coast and Alaska Fisheries over four decades

2025· article· en· W4406090814 on OpenAlexvenueno aff
Daniel S. Holland, Stephen Kasperski, Joshua K. Abbott

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsnot available
FundersNational Oceanic and Atmospheric Administration
KeywordsFisheryFishingWest coastFisheries managementGeographyEcologyBiologyOceanography

Abstract

fetched live from OpenAlex

Access to West Coast and Alaskan fisheries has been progressively tightened for more than four decades with limited license programs, buybacks, and catch share programs. We document the implementation of a series of limited access and catch share programs in federally and state managed fisheries of the West Coast and Alaska, and evaluate trends in participation, diversification, vessel revenue, and variation of revenue between 1981 and 2022 for this large interconnected system of fisheries. Over time, progressive tightening through further input controls, buybacks, and catch shares led to substantial consolidation and greater specialization coinciding with increased temporal diversification, maintained or increased revenue per vessel, and reduced variation in inter-annual revenue. However, low levels of fishery diversification for many fishers, and high dependency on a few key fisheries, may have left fishers vulnerable to ecological and economic shocks that impacted key fisheries leading to increased income variation and further declines in participation in recent years.

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)0.025
metaresearch head score (Gemma)0.036
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 score0.936
Threshold uncertainty score0.133

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.036
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.030
GPT teacher head0.314
Teacher spread0.284 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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