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Record W4296025569 · doi:10.1038/s44183-022-00001-7

Social equity is key to sustainable ocean governance

2022· article· en· W4296025569 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

Venuenpj Ocean Sustainability · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal and Marine Management
Canadian institutionsUniversité LavalThe Quebec Population Health Research NetworkDalhousie UniversityMemorial University of NewfoundlandUniversity of British ColumbiaFisheries and Oceans Canada
FundersEarthLab, University of WashingtonOcean Nexus Center, EarthLab, University of WashingtonConsortium of International Agricultural Research CentersUniversity of Washington
KeywordsOperationalizationEquity (law)Corporate governancePrivate equity fundBusinessPolitical sciencePublic economicsEconomicsFinancePrivate equityLaw

Abstract

fetched live from OpenAlex

Abstract Calls to address social equity in ocean governance are expanding. Yet ‘equity’ is seldom clearly defined. Here we present a framework to support contextually-informed assessment of equity in ocean governance. Guiding questions include: (1) Where and (2) Why is equity being examined? (3) Equity for or amongst Whom ? (4) What is being distributed? (5) When is equity considered? And (6) How do governance structures impact equity? The framework supports consistent operationalization of equity, challenges oversimplification, and allows evaluation of progress. It is a step toward securing the equitable ocean governance already reflected in national and international commitments.

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 categoriesMeta-epidemiology (narrow), Open science, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.128
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.028
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.000

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 head0.008
GPT teacher head0.257
Teacher spread0.249 · 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