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Record W4394772367 · doi:10.5376/ijms.2024.14.0010

The Impact of Socio-Economic Factors on the Decline of Fishery Resources

2024· article· en· W4394772367 on OpenAlex
Heng Han, Zixu Chen

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Marine Science · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Bivalve and Aquaculture Studies
Canadian institutionsnot available
Fundersnot available
KeywordsOverfishingSustainabilityLivelihoodProsperityNatural resource economicsBusinessFisheries managementMarine conservationContext (archaeology)FisheryEnvironmental resource managementEconomicsFishingGeographyEconomic growthEcologyAgriculture

Abstract

fetched live from OpenAlex

The decline of fishery resources poses a serious challenge to the global marine ecosystem and socio-economic system. Socio economic factors play an important role in this issue and have a profound impact on the health and sustainability of fishery resources. The closely intertwined relationship between fisheries and socio-economic factors has become increasingly significant in the current global environmental context. The impact of socio-economic factors on the decline of fishery resources is mainly reflected in the livelihoods of fishermen, the protection of fishery practitioners by social policies, and overfishing behavior caused by economic development pressure. Although economic development brings prosperity to society, it may also trigger excessive dependence on fishery resources, accelerating the decline of resources. This review focuses on elucidating how socio-economic factors directly affect the health and sustainability of fishery resources, providing a profound understanding and insights for developing more forward-looking and feasible fisheries management policies.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.097
Threshold uncertainty score0.862

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.301
Teacher spread0.286 · 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