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Record W4409121337 · doi:10.3917/mouv.119.0031

La posture alliée en recherche : des savoirs par, pour et avec les autochtones au Canada

2025· article· fr· W4409121337 on OpenAlexaboutno aff
Joannie Gill, Amélie Blanchet Garneau, Christine Cassivi, Shenda Collin

Bibliographic record

VenueMouvements · 2025
Typearticle
Languagefr
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceArt

Abstract

fetched live from OpenAlex

Au Canada, l’histoire coloniale et ses effets contemporains dans les communautés autochtones ont conduit à l’élaboration d’approches de recherche par, pour et avec les autochtones. Ces approches reposent notamment sur des méthodologies de co-production des savoirs, la propriété des données par les communautés autochtones et la dimension transformatrice du processus de recherche. Cette épistémologie pluraliste valorise les savoirs autochtones qui intègrent des dimensions spirituelles, culturelles et environnementales inséparables de leur contexte d’élaboration. En plus de présenter ces dimensions, cet article approfondit l’analyse des défis de la co-production des connaissances entre autochtones et allochtones dans le domaine de la santé, sous l’angle de la posture alliée en recherche.

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)0.013
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.979
Threshold uncertainty score0.485

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0210.043
Scholarly communication0.0100.003
Open science0.0010.006
Research integrity0.0020.003
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 head0.131
GPT teacher head0.424
Teacher spread0.293 · 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.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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