MétaCan
Menu
Back to cohort
Record W4389105672 · doi:10.53555/sfs.v9i1.1796

Navigating Global Waters: Exploring International Dimensions of Fisheries Legislation

2022· article· en· W4389105672 on OpenAlexvenueno aff
Ashok Kumar Karnani -

Bibliographic record

VenueJournal of Survey in Fisheries Sciences · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicInternational Maritime Law Issues
Canadian institutionsnot available
Fundersnot available
KeywordsOverfishingFisheries lawFishingFisheries managementLegislationSafeguardingBusinessFisheryEnforcementInternational lawFish stockInternational watersSustainabilityEnvironmental resource managementPolitical scienceEconomicsLawEcology

Abstract

fetched live from OpenAlex

This abstract delves into the multifaceted and consequential nature of fishery law on a global scale. The present abstract emphasizes the significance of global collaboration in the management of fisheries resources and the maintenance of sustainable fishing methods. It also covers how international agencies like the Food and Agriculture Organization and the United Nations formulate and carry out fisheries laws and regulations. The abstract highlights the necessity of strong enforcement measures to guarantee adherence to international fisheries regulations and stop overfishing and fish supply depletion. It also looks at how international agreements and organizations have influenced the development of fishery law and encouraged ethical fishing methods. Overall, this abstract emphasizes the vital role that international fisheries legislation plays in encouraging ethical fishing methods and safeguarding the world's fisheries resources for coming generations.

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)0.008
metaresearch head score (Gemma)0.010
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 score0.017
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.004
Science and technology studies0.0060.024
Scholarly communication0.0140.015
Open science0.0010.009
Research integrity0.0030.005
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 head0.150
GPT teacher head0.296
Teacher spread0.146 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Survey in Fisheries SciencesSame topicInternational Maritime Law IssuesFrench-language works237,207