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Record W4404444160 · doi:10.37870/joqie.v14i24.452

Le Canada comme partie prenante en matière de coopération Universitaire multilatérale

2024· article· fr· W4404444160 on OpenAlexaboutno aff
René Rodrigue Lionel Kana Etoundi

Bibliographic record

VenueThe Journal of Quality in Education · 2024
Typearticle
Languagefr
FieldHealth Professions
TopicHealthcare Systems and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

La présente réflexion questionne la participation du partenaire Canadien dans le programme de coopération universitaire panafricain de l’Institut Africain des Sciences Mathématiques (AIMS). Fondé à Cape Town en Afrique du Sud en 2003, c’est en Juillet 2013 que le centre d’excellence au Cameroun ouvre ses portes. Ce programme international connait une participation effective de plusieurs parties prenantes. Parmi celles-ci, figure le Canada. La coopération au tour de cette initiative permet de proposer des activités de formation universitaire avec un encadrement novateur et environnement d’apprentissage moderne. Cependant dans quel registre du rapport coopératif faut-il inscrire la participation du partenaire canadien ? L’objectif de cet article est de mener une réflexion critique en vue de l’amélioration du partenariat multilatéral en matière de coopération universitaire en Afrique. La démarche empirico-inductive. L’étude est qualitative et exploratoire. L’approche Oumarienne (2022) de la théorie des parties prenantes permet de construire une analyse critique des contenus et des données issues des entretiens. En résultat, la présentation du programme laisse entrevoir un déploiement financier important de la part du Centre de Recherche et de Développement International canadien. L’analyse diachronique de cet apport montre que le programme panafricain est financièrement dépendant de l’apport canadien.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: none
Teacher disagreement score0.557
Threshold uncertainty score0.974

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.136
GPT teacher head0.487
Teacher spread0.352 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2024
Admission routes1
Has abstractyes

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