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Record W3118007216 · doi:10.5663/aps.v9i1.29364

Freins à la mise en œuvre en contexte canadien de la Déclaration des Nations Unies sur les droits des Peuples autochtones

2020· article· fr· W3118007216 on OpenAlexaffvenueabout
Karine Gentelet, Maria Samson

Bibliographic record

Venueaboriginal policy studies · 2020
Typearticle
Languagefr
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversité du Québec en Outaouais
Fundersnot available
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

Cet article propose une revue de littérature des enjeux freinant la mise en œuvre de la Déclaration des Nations Unies sur les droits des Peuples autochtones en contexte canadien. Adoptée en 2007, cela fait plus de dix années que des processus de mise en œuvre ont été initiés un peu partout au pays. Cet article constitue ainsi l’opportunité de revenir sur ces dix années et d’en dresser un bilan. Trois types d’enjeux ont été répertoriés, liés à la nature, au contenu et encore à l’utilisation de la Déclaration. A ces enjeux, se rajoute la question de la réconciliation en tant que frein consubstantiel au contexte canadien. Le concept de réconciliation, fortement mobilisé ces dernières années par le gouvernement fédéral pour justifier un certain nombre de pratiques, suggère un cadre référentiel de mise en œuvre beaucoup plus restrictif puisque circonscrit uniquement au cadre politique interne canadien et limitant de fait la reconnaissance des droits politiques des Peuples autochtones.

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)0.016
metaresearch head score (Gemma)0.023
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.985
Threshold uncertainty score0.223

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.023
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0110.022
Scholarly communication0.0100.006
Open science0.0020.008
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0070.001

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 head0.064
GPT teacher head0.416
Teacher spread0.353 · 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

Citations1
Published2020
Admission routes3
Has abstractyes

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