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Record W1811201853 · doi:10.7202/012602ar

Co-création d’un espace-temps de guérison en territoire ancestral par et pour les membres d’une communauté autochtone au Québec

2006· article· fr· W1811201853 on OpenAlexvenueaboutno aff
Pierre St-Arnaud, Pierre Bélanger

Bibliographic record

VenueDrogues santé et société · 2006
Typearticle
Languagefr
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArtPhysics

Abstract

fetched live from OpenAlex

Brisures dans les tissus social et familial, violence physique et sexuelle, isolement, taux de suicide élevé et surconsommation de drogues et d’alcool accompagnent souvent le portrait de bon nombre de communautés autochtones du Canada. L’abus de substances a longtemps été identifié comme une des causes fondamentales des divers troubles rencontrés chez les Autochtones. En regardant la situation avec une ouverture historique et sociale, on constate rapidement que cette surconsommation est en fait bien plus un symptôme qu’une cause en soi. S’appuyant sur cette observation et sensibilisées à l’héritage du passé, à la transmission intergénérationnelle et au potentiel de guérison, les forces internes émergentes de la communauté de Nutashkuan, aidées de psychologues, ont mis sur pied un projet de guérison, basé sur des expéditions thérapeutiques sur le territoire du Nistassinan. Investi au départ par les problématiques de surconsommation, ce projet s’est peu à peu transformé en un véritable espace de co-création orienté vers les solutions. Aujourd’hui, ce ne sont plus les effets destructeurs d’abus de substances qui sont au centre des préoccupations, mais plutôt le développement des éléments de bien-être et de protection qui trouvent leur expression dans l’harmonie familiale et la paix sociale.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.233
Threshold uncertainty score0.469

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0160.007
Scholarly communication0.0030.001
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0160.001

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 head0.031
GPT teacher head0.390
Teacher spread0.359 · 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

Citations11
Published2006
Admission routes2
Has abstractyes

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