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Record W4400324304 · doi:10.1515/9782760560390

S'ouvrir aux Amériques

2024· book· fr· W4400324304 on OpenAlexaboutno aff
Bernard Duhaime

Bibliographic record

VenuePresses de l'Université du Québec eBooks · 2024
Typebook
Languagefr
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Le projet S’ouvrir aux Amériques (SOAA) est un projet de recherche universitaire dont la vocation est de mettre de l’avant le transfert de connaissances du Sud vers le Nord. La conviction qui guide ce projet est que la société canadienne peut apprendre beaucoup de l’expérience des institutions publiques et des organisations latino-américaines de défenses des droits de la personne, entre autres en ce qui a trait aux interactions de celles-ci avec les mécanismes internationaux de protection des droits. Les meilleures pratiques latino- américaines en matière de justice transitionnelle sauraient par ailleurs enrichir les débats qui ont actuellement cours au Canada. Ce rapport, divisé en sept chapitres, s’appuie sur les avis reçus lors de sondages, de rencontres et d’évènements nationaux s’étant tenus entre l’automne 2017 et l’automne 2019 avec le soutien financier de la Fondation Pierre Elliott Trudeau. Ces avis ont donné lieu à un ensemble de réflexions qui structurent ce rapport et qui sont le fruit de l’interaction avec différentes parties prenantes impliquées dans la promotion et la protection des droits de la personne.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.290
Threshold uncertainty score0.577

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.002
Scholarly communication0.0050.004
Open science0.0010.004
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0580.009

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 head0.077
GPT teacher head0.330
Teacher spread0.253 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2024
Admission routes1
Has abstractyes

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