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Record W4386692664 · doi:10.3368/aa.59.1.87

An Examination of Indigenous Halibut Fishing Technology on the Northwest Coast of North America

2023· article· en· W4386692664 on OpenAlexafffund
Jacob Ulrich Salmen-Hartley, Iain McKechnie

Bibliographic record

VenueArctic Anthropology · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsUniversity of VictoriaParks Canada
FundersHakai Institute
KeywordsHalibutFishingFisheryHookIndigenousBycatchGeographyEcologyFish <Actinopterygii>Biology

Abstract

fetched live from OpenAlex

<h3>Abstract</h3> As global fish populations face threats from climatic change and human exploitation, the value of Indigenous knowledge and technology for guiding restoration and conservation efforts is gaining increasing recognition. Indigenous fishers on the Northwest Coast of North America traditionally employed sophisticated harvesting practices developed through long-term relationships with marine ecosystems, which promoted sustained harvests. Here we examine traditional Pacific halibut (<i>Hippoglossus stenolepis</i>) hook technology which has been shown to reduce bycatch of nontarget species and is often described as highly size-selective. We investigate this technology using ethnographic information, analysis of fishing equipment curated in museums, and measurements of modern halibut. We identify regional variation and overlap in hook styles, expand previously established hook typologies, and observe the greatest number of hooks and the most stylistic diversity originating from Haida Gwaii, a location where available zooarchaeological data indicates high halibut abundance. We demonstrate that two measurements (hook lip-gap and barb-area size) disproportionately influence the maximum and minimum body size. Based on hook and modern fish measurements, we estimate the sample of hooks targeted fish between 53 and 145 cm in length, indicating a broad but flexible size-selectivity that has presentday relevance for fisheries conservation, including nonmortality slot-limit fishing.

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.125
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.272
Teacher spread0.256 · 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 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

Citations4
Published2023
Admission routes2
Has abstractyes

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