MétaCan
Menu
Back to cohort

PAST AND FUTURE MANAGEMENT OF A COLLAPSED FISHERY: THE BAY OF BISCAY ANCHOVY

2012· article· en· W1507112570 on OpenAlexaff
Itziar Lazkano, Linda Nøstbakken, Raúl Prellezo

Bibliographic record

VenueNatural Resource Modeling · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAnchovyFisheryStock (firearms)BayFish stockFisheries managementBusinessFish <Actinopterygii>OceanographyGeographyFishingBiology

Abstract

fetched live from OpenAlex

Abstract We analyze the efficiency of the international management of the Bay of Biscay anchovy. While a sharing agreement between France and Spain has been in place since 1992, the fish stock collapsed in 2005 and the fishery closed from 2005 to spring 2010. We consider differences in production technologies between both countries and calibrate our model using data from 1987 to 2009. Our results suggest two sources of rent dissipation under the existing sharing agreement: inefficient quota allocation and production inefficiencies due to inflexible national regulations. We discuss several alternatives to improve management.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.122
Threshold uncertainty score0.242

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
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 head0.012
GPT teacher head0.233
Teacher spread0.220 · 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 designSimulation or modeling
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

Citations10
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueNatural Resource ModelingSame topicMarine and fisheries researchFrench-language works237,207