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Record W4415858222 · doi:10.1139/facets-2025-0042

Indigenous stream caretaking for Pacific salmon: ancestral lifeways to guide restoration, relationships, rights, and responsibilities

2025· article· en· W4415858222 on OpenAlexafffundvenue
Kirsten Bradford, Kii'iljuus Barbara Wilson, Emma E. Hodgson, Jonathan W. Moore, Andrea J. Reid, Anne K. Salomon, Colton Van Der Minne, Jeannette Armstrong, Kari I. Alex, R E Benson, Jared Dick

Bibliographic record

VenueFACETS · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of VictoriaSimon Fraser UniversityOkanagan CollegeFisheries and Oceans CanadaUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersFisheries and Oceans CanadaCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada
KeywordsIndigenousHabitatCorporate governanceTraditional knowledgeIndigenous rights

Abstract

fetched live from OpenAlex

Restoring the relationships, rights, and responsibilities of Indigenous Peoples to their salmon kin is central to a sustainable and just future with Pacific salmon, particularly as Nations lead the restoration of freshwater salmon habitat in their territories. As a group of Indigenous and non-Indigenous researchers from across British Columbia, we come together in a respectful and transparent way to uphold ancestral Indigenous Pacific salmon stream caretaking knowledge, longstanding Indigenous rights and relationships to land and waters, and our joint responsibilities to care for these watersheds. To do this, we begin by describing traditional governance systems that house Indigenous salmon stream caretaking practices. Through a literature review and conversations with co-authors, we then describe eight Indigenous salmon stream caretaking practices. Finally, we share three contemporary focal stories of Indigenous salmon restoration projects that uphold ancestral knowledge; “Syilx sockeye restoration”, “səlilwətaɬ (Tsleil-Waututh) led salmon habitat restoration in xʔə’l̓ilwətaʔɬ (Indian River Watershed)”, and nuučaanuɫ (Nuu-chah-nulth) Peoples and salmon: responsive methods through steadfast lifeways’. We present stream caretaking knowledge and the focal stories as learning opportunities that may guide future human-salmon relationships and restoration.

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 score0.046
Threshold uncertainty score0.848

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 head0.021
GPT teacher head0.269
Teacher spread0.248 · 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

Citations1
Published2025
Admission routes3
Has abstractyes

Explore more

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