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Record W3091753970 · doi:10.1007/s11625-020-00865-z

Ambitious subsidy reform by the WTO presents opportunities for ocean health restoration

2020· article· en· W3091753970 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.

Bibliographic record

VenueSustainability Science · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsUniversity of British ColumbiaFisheries and Oceans Canada
FundersPew Charitable Trusts
KeywordsSubsidyFishingBusinessSustainable developmentWork (physics)International tradeEconomicsNatural resource economicsFisheryPublic economicsEcologyBiologyEngineering

Abstract

fetched live from OpenAlex

Abstract The World Trade Organization (WTO) is in a unique position to deliver on Sustainable Development Goal (SDG) 14.6 by reforming global fisheries subsidies in 2020. Yet, a number of unanswered questions threaten to inhibit WTO delegates from crafting a smart agreement that improves global fisheries health. We combine global data on industrial fishing activity, subsidies, and stock assessments to show that: (1) subsidies prop up fishing effort all across the world’s ocean and (2) larger subsidies tend to occur in fisheries that are poorly managed. When combined, this evidence suggests that subsidy reform could have geographically-extensive consequences for many of the world’s largest fisheries. While much work remains to establish causality and make quantitative predictions, this evidence informs the rapidly-evolving policy debate and we conclude with actionable policy suggestions.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.475
Threshold uncertainty score0.564

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.220
GPT teacher head0.318
Teacher spread0.098 · 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