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Record W4214676942 · doi:10.22434/ifamr2021.0059

The apparent conflict of Norwegian pelagic fisheries management and Norwegian seafood council export promotion

2022· article· en· W4214676942 on OpenAlexaff
Gary W. Williams, Oral Capps

Bibliographic record

VenueThe International Food and Agribusiness Management Review · 2022
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsRegent College
FundersNational Science Council
KeywordsHerringMackerelNorwegianPelagic zoneFisheryProfit (economics)RevenueBusinessFisheries managementPromotion (chess)EconomicsFish <Actinopterygii>FishingAccountingBiologyPolitical science

Abstract

fetched live from OpenAlex

The Norwegian government operates pelagic fishery management systems designed to avoid overfishing and foster sustainable annual landings while at the same time managing an export promotion program designed to increase foreign sales of herring and mackerel. Simultaneously promoting foreign sales of pelagic fish and limiting the availability of those fish for sale are policies in apparent conflict. This research demonstrates, however, that effective limits on the availability of pelagic fish for export tend to complement the profitenhancing export promotion objectives of the Norwegian Seafood Council (NSC) for the Norwegian herring and mackerel industries. Assuming highly (but not perfectly) effective limits on herring and mackerel exports arising from their respective fishery management systems over the 2003 to 2018 period of analysis, NSC herring and mackerel export promotion contributed 5-7% to Norwegian herring export revenue and industry profit, respectively and 11-15% to Norwegian mackerel export revenue and industry profit, respectively. Less effective limitation on Norwegian herring and mackerel export supplies would erode the respective industry revenue and profit gains from NSC export promotion. In essence, the NSC effectively exploits the limits on herring and mackerel export availability imposed by Norwegian fishery management systems for the benefit of Norwegian herring and mackerel industries.

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 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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.938
Threshold uncertainty score0.459

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.099
GPT teacher head0.222
Teacher spread0.123 · 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 teacher head, 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

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