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Record W2568665805 · doi:10.7202/1037509ar

Présentation

2016· article· fr· W2568665805 on OpenAlexaffvenueabout
Emmanuelle Piccoli, Geneviève Motard, Christoph Eberhard

Bibliographic record

VenueAnthropologie et Sociétés · 2016
Typearticle
Languagefr
FieldSocial Sciences
TopicMulticulturalism, Politics, Migration, Gender
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

En 2015, la Commission de vérité et de réconciliation du Canada (CVRC) soulignait l'importance de la prise en compte du droit pour établir la vérité et parvenir à la réconciliation entre les peuples autochtones et la société dominante.Elle relevait aussi que le droit étatique avait été utilisé comme un outil d'oppression et avait largement contribué à invalider les règles et principes des ordres juridiques autochtones.Or, si effectivement « une meilleure compréhension et la poursuite du développement du droit autochtone [offraient] des ressources inestimables pour la prise de décision, la réglementation et la résolution de conflits » (CVRC 2015 : 53), on mesure l'importance des enjeux et les défis qu'entraîne la mise en place d'un pluralisme juridique effectif aujourd'hui.Ces questions de rapports de force, de relations entre les ordres juridiques et de leurs effets sur les personnes sont au centre de ce numéro, qui aborde les rencontres entre les juridicités autochtones et étatiques, mais aussi les pratiques et transformations du/des « D/droit/s » 2 dans des situations de migration et d'interculturalité.

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)0.004
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.386
Threshold uncertainty score0.876

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0060.001
Scholarly communication0.0080.003
Open science0.0020.005
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.3860.147

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 head0.449
GPT teacher head0.636
Teacher spread0.186 · 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 designNot applicable
Domainnot available
GenreEditorial

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
Published2016
Admission routes3
Has abstractyes

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Same venueAnthropologie et SociétésSame topicMulticulturalism, Politics, Migration, GenderFrench-language works237,207