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Record W4409158186 · doi:10.1016/j.exis.2025.101653

Expectations for meaningful free, prior, and informed consent: an exploration by the Little Salmon/Carmacks First Nation

2025· article· en· W4409158186 on OpenAlexafffundabout
Emily M.W. Martin, The Little Salmon Carmacks First Nation, Ben Bradshaw

Bibliographic record

VenueThe Extractive Industries and Society · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsUniversity of Guelph
FundersSocial Sciences and Humanities Research CouncilPolar Knowledge Canada
KeywordsInformed consentPsychologyBusinessPolitical scienceFisherySocial psychologyEnvironmental ethicsBiologyPhilosophyMedicine

Abstract

fetched live from OpenAlex

Indigenous self-determination plays an increasingly prominent role in lands and resources development decisions. One way of operationalizing self-determination is through the realization of free, prior, and informed consent (FPIC) for development impacting Indigenous Peoples and their lands, as recognized in the United Nations Declaration on the Rights of Indigenous peoples (UNDRIP). In the Yukon, Canada, where some consent and consent-like rights are held by First Nations, few First Nations have formally articulated their expectations for the meaningful expression of their consent. This paper begins to address this gap based on a case study by the Little Salmon/Carmacks First Nation (LS/CFN), a self-governing, Northern Tutchone Yukon First Nation located proximate to past, present, and potentially future mineral development. Though LS/CFN's expectations of FPIC are not formalized today, this exploratory research presents that LS/CFN participants expect: early engagement; to be fully informed; space for self-defined internal processes; ongoing engagement with proponents and the Crown; mitigation of resource barriers; enforceability of commitments; contextually relevant processes; appropriate representation; agreed upon definitions of terminology; mitigation of power imbalances; and mutual agreement on the consent process itself. More broadly this article makes a case for a covenantal, rather than a solely contractual, approach to make FPIC meaningful.

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)0.058
metaresearch head score (Gemma)0.041
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.913
Threshold uncertainty score0.305

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0580.041
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0230.040
Scholarly communication0.0120.008
Open science0.0020.011
Research integrity0.0060.009
Insufficient payload (model declined to judge)0.0020.000

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 head0.067
GPT teacher head0.349
Teacher spread0.282 · 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 designQualitative
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

Citations2
Published2025
Admission routes3
Has abstractyes

Explore more

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