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The impact of subsidies upon fisheries management and sustainability: the case of the North Atlantic

2002· article· en· W2043992590 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueFish and Fisheries · 2002
Typearticle
Languageen
FieldEnergy
TopicEnergy, Environment, and Transportation Policies
Canadian institutionsUniversity of British Columbia
FundersWorld Wildlife FundUniversity of British ColumbiaPew Charitable Trusts
KeywordsSubsidyFisherySustainabilityHarmFisheries managementFisheries lawNatural resource economicsBusinessGovernment (linguistics)EconomicsPublic economicsEnvironmental resource managementEcologyFishingPolitical science

Abstract

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Abstract This paper provides both an estimate and assessment of subsidies in fisheries in the North Atlantic. The subsidies are estimated, on the basis of data taken from an OECD study and the Sea Around US Project database, to be in the order of US$ 2.0–2.5 billion per year. The assessment of the impact of the subsidies upon resource management and sustainability requires an examination of the underlying economics of subsidies in fisheries. There is general agreement, to which we subscribe, that fisheries subsidies do great harm by exacerbating the problems arising from the ‘common pool’ aspects of capture fisheries. Many economists, however, believe it that, if the ‘common pool’ aspects of a fishery could be removed by, for example, establishing a full‐fledged property rights system, the negative impact of fisheries subsidies would prove to be trivial. This paper demonstrates that the aforementioned comfortable belief is unfounded. Fisheries subsidies can be seriously damaging, even if the ‘common pool’ aspects of the fishery are removed. There is also a widely held belief among economists and government officials that subsidies used for vessel decommissioning schemes, far from being harmful, actually have a beneficial impact upon resource management and sustainability, or are at worst, neutral. About 20% of the fisheries subsidies in the North Atlantic are directed towards these purposes. In this paper, we argue that these seemingly beneficial subsides can, in fact, be highly negative in their impact.

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)0.000
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 score0.030
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.009
GPT teacher head0.203
Teacher spread0.194 · 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