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Record W3157148298 · doi:10.1139/facets-2020-0080

Understanding barriers, access, and management of marine mixed-stock fisheries in an era of reconciliation: Indigenous-led salmon monitoring in British Columbia

2021· article· en· W3157148298 on OpenAlexaffvenueabout
Jade Steel, William I. Atlas, Natalie C. Ban, Kyle L. Wilson, Jayda Wilson, William Housty, Jonathan W. Moore

Bibliographic record

VenueFACETS · 2021
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsSimon Fraser UniversityUniversity of Victoria
Fundersnot available
KeywordsFisheryIndigenousLivelihoodFishingFisheries managementStock (firearms)GeographyFish stockFood securityBusinessEcologyAgricultureBiology

Abstract

fetched live from OpenAlex

Wild salmon are central to food security, cultural identity, and livelihoods of coastal Indigenous communities. Yet ongoing inequities in governance, declining fish populations, and mixed-stock ocean fisheries may pose challenges for equitable access between Indigenous fishers and other non-Indigenous fishers. We sought to understand current perceptions among Haíłzaqv (Heiltsuk) fishers towards salmon fisheries and their management. We conducted dockside surveys with both Haíłzaqv fishers and sport fishers, and in-depth interviews with Haíłzaqv fishers, community members, and natural resource managers. From these surveys and interviews we quantified satisfaction among both food, social, and ceremonial fishers and visiting recreational fishers with the current salmon fishery and associated social-ecological drivers, and characterized perceptions among Haíłzaqv people of salmon fisheries and management. Second, we synthesized community perceptions of the revitalization of terminal, communally run salmon fisheries within Haíłzaqv territory as a tool for their future salmon management. Finally, we elicited information from Haíłzaqv fishers about the barriers people in their community currently face in accessing salmon fisheries. Our findings suggest that low salmon abundance, increased fishing competition, and high costs associated with participation in marine mixed-stock fisheries currently hinder access and equity for Haíłzaqv fishers. This community-based research can help strengthen local, Indigenous-led management of salmon into the future.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.857
Threshold uncertainty score0.955

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.092
GPT teacher head0.351
Teacher spread0.260 · 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.

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

Citations22
Published2021
Admission routes3
Has abstractyes

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