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Record W3191884201 · doi:10.1111/faf.12602

Small‐scale fisheries and local food systems: Transformations, threats and opportunities

2021· article· en· W3191884201 on OpenAlexaff
Robert Arthur, Daniel J. Skerritt, Anna Schuhbauer, Naazia Ebrahim, Richard Friend, U. Rashid Sumaila

Bibliographic record

VenueFish and Fisheries · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicCoral and Marine Ecosystems Studies
Canadian institutionsMembrane Reactor Technologies (Canada)University of British ColumbiaFisheries and Oceans Canada
Fundersnot available
KeywordsFood securityFood systemsBusinessCorporate governanceFisheries lawPovertyFisheries managementScale (ratio)FisheryFisheries scienceSustainabilityEnvironmental resource managementEconomicsEconomic growthGeographyEcologyFishingAgricultureBiology

Abstract

fetched live from OpenAlex

Abstract Fish from marine and inland capture fisheries is an important food that contributes significantly to diets and health, but their contribution is somewhat overlooked in food security and poverty‐related policies. Given the current numbers of malnourished people globally, there is a pressing need to consider how to better realize the potential of fish in food systems that can address malnourishment. To do so, we re‐examine the fisheries literature from the perspective of food systems. Starting with nutritional needs and considering how these may be met through local food systems reveals an ongoing transformation that has implications for small‐scale fisheries, as increasingly become part of globalized food systems. We describe the factors that can change the nature of production, mediate access to fish and the distribution of benefits that can lead to impoverishment. This emphasizes the governance challenges that lie at the heart of complex, contested and increasingly globalized food systems, in which actors interact to shape the systems, determining who benefits and how. We draw attention to critical issues of access, power and the values and norms that underpin efforts to manage and transform fisheries, exposing the unequal struggle to secure access that small‐scale fishers and poor people must endure. We suggest a vital challenge for fisheries management is to engage with this struggle and develop policies and management measures that would enable fisheries to make positive contributions to food systems and nutritional security, while meeting global sustainable development objectives.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.008
Scholarly communication0.0040.003
Open science0.0000.005
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.000

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 head0.037
GPT teacher head0.188
Teacher spread0.151 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations132
Published2021
Admission routes1
Has abstractyes

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