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Record W2337321762

Opportunities for Sustainable Livelihoods in the Southwest Coast Lobster Fishery

2010· article· en· W2337321762 on OpenAlexaboutno aff
Katie Temple

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsnot available
Fundersnot available
KeywordsFisheryFishingAmerican lobsterHomarusBusinessEnvironmental scienceBiologyCrustacean
DOInot available

Abstract

fetched live from OpenAlex

Fish harvesters on the southwest coast of Newfoundland depend heavily on lobster to earn a living. In recent years, decreasing prices and other challenges have threatened the viability of the industry and the future employment of many harvesters’ families and others dependent on the small boat fishery. In the past few years southwest coast fishermen have had high average lobster catch rates per harvester and the number of active licenses in the region has been stable. Most of the lobster is sold to two local buyers and then exported, primarily to the United States. The Department of Fisheries and Oceans is the main regulator for harvesting, while the Department of Fisheries and Aquaculture regulates the industry post-harvest. Currently the environmental sustainability of the fishery is in question because although there are a number of conservation methods in place, exploitation rates are very high. Low prices contribute to the pressure on harvesters to fish intensively.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.975
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0160.001

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 head0.041
GPT teacher head0.248
Teacher spread0.207 · 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

Citations0
Published2010
Admission routes1
Has abstractyes

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