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Record W4407319265 · doi:10.1093/fshmag/vuae031

Provisioning fisheries: A framework for recognizing the fuzzy boundary around commercial, subsistence, and recreational fisheries

2025· article· en· W4407319265 on OpenAlex
Vivian M. Nguyen, Kathryn J. Fiorella, Leandro Castello, Mahatub Khan Badhon, Christine Beaudoin, Jeanne Coffin-Schmitt, Steven J. Cooke, Aaron T. Fisk, Elizabeth A. Nyboer, Daniel M. O’Keefe, Emma Rice, Richard C. Stedman, Nicole Venker, Aaron MacNeil

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

VenueFisheries · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal and Marine Management
Canadian institutionsDalhousie UniversityUniversity of WindsorCarleton University
Fundersnot available
KeywordsSubsistence agricultureFisheryProvisioningRecreational fishingFisheries managementBusinessFisheries scienceFishingGeographyEcologyBiologyComputer scienceAgriculture

Abstract

fetched live from OpenAlex

ABSTRACT Although sparse, increasing evidence suggests an overlooked population of fishers whose fishing motivations and outcomes overlap across commercial, subsistence and recreational fishing sectors, resulting in underrepresented groups of fishers in management and policy frameworks. These fishers participate in what we frame as “provisioning fisheries,” a concept we propose to highlight the underrepresented values from fishing and fisheries across recreational, sociocultural, psychological, economic, health, and nutritional dimensions. We argue that provisioning fisheries often support underserved groups, provisioning fishers may engage in informal markets, and, that distinction exists from sport-oriented recreational fisheries in power, risks, access barriers, fishing motivation, attitudes, and practices including rule and advisory awareness. We propose that provisioning fisheries should be consciously considered—whether as part of existing fisheries structures or even its own sector to promote more sustainable and inclusive fisheries management. Overlooking this population of fishers may risk further marginalization, conflicts, contaminant exposure, and inaccurate stock estimates. Therefore, we propose provisioning fisheries as a useful analytical category to explore the heterogeneity of fishers and their distinct needs, motivations, and behaviors. As an example of how these fisheries may function, we synthesize what we currently know about provisioning fisheries in North America with hypothesized differences between provisioning and the sport-oriented recreational fisher to encourage greater dialogue and investigation about underrecognized fisheries.

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)0.000
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 score0.648
Threshold uncertainty score0.834

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 studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.245
Teacher spread0.225 · 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