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Record W4414116748 · doi:10.1016/j.marpol.2025.106898

Beyond growth: Reshaping fisheries for a wellbeing economy

2025· article· en· W4414116748 on OpenAlexaff
Ingrid Kelling, Nathan Bennett, Kate Barclay, Andrew Jeffs, Cristina Pita, Birgitte Krogh-Poulsen, Tobias Troll, Evgenia Micha, Julia Cirne Lima Weston, Iain Black, Ibrahim Lawan, Alexandra Leeper, Nicky Pouw, Melanie Siggs, Kazumi Wakita

Bibliographic record

VenueMarine Policy · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsFisheries and Oceans Canada
FundersOrganisation de Coopération et de Développement ÉconomiquesHeriot-Watt University
KeywordsProsperityLivelihoodSustainabilityIntergenerational equityEquity (law)DignityFisheries lawSustainable development

Abstract

fetched live from OpenAlex

Contemporary fisheries have been shaped by a paradigm of perpetual growth, characterized by increasing global production and consumption. While this growth has driven economic benefits and technological progress, it has jeopardized the sustainability of marine ecosystems, with implications for the long-term livelihoods and wellbeing of fishers, consumers and resource dependent coastal populations worldwide. This paper advocates for a shift beyond growth towards a wellbeing economy. It considers how five fundamental principles intrinsic to a wellbeing economy - purpose, nature, fairness, participation and dignity - can help reorient the fisheries sector. The paper then provides ten actionable recommendations for reshaping the composition and structure of economic activity in fisheries to enhance societal wellbeing and equity within ecological boundaries. In a world grappling with the consequences of unchecked economic growth, this paper offers insights into fostering a regenerative fisheries system that safeguards human prosperity and environmental integrity.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.743
Threshold uncertainty score0.998

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.012
GPT teacher head0.266
Teacher spread0.254 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations2
Published2025
Admission routes1
Has abstractyes

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