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Record W7067095592

La coopération au service de l’apprentissage durable

2024· article· fr· W7067095592 on OpenAlexaboutno aff

Bibliographic record

VenuePapyrus : Institutional Repository (Université de Montréal) · 2024
Typearticle
Languagefr
FieldSocial Sciences
TopicCollaborative Teaching and Inclusion
Canadian institutionsnot available
Fundersnot available
KeywordsIle de franceSocial impactService (business)Population
DOInot available

Abstract

fetched live from OpenAlex

La coopération, compétence fondamentale \ndu 21e siècle, parait dans le \nProgramme de formation de l’école québécoise \nà titre de compétence d’ordre \npersonnel et social à développer dès \nl’éducation préscolaire (Gouvernement \ndu Québec, 2006 ; 2021). La coopération \nest une avenue à considérer pour \noffrir aux élèves différents contextes \nde pratique (voir l’article sur la répétition, \nCarpentier et al., 2023a) et un \nsoutien socioaffectif susceptible d’aider \nau maintien de leur attention sur \nla tâche (voir l’article sur l’attention, \nCarpentier et al., 2024). De plus, la \ncoopération offre des contextes où les \nélèves peuvent accéder à la réflexion \nde leurs pairs, être regroupés selon \nleurs forces et besoins et bénéficier \nd’un soutien en cours d’apprentissage \n(voir l’article sur la zone proximale de \ndéveloppement [ZPD], Carpentier et \nal., 2 023b). Ainsi, les personnes enseignantes \ngagnent à mettre en place \ndes pratiques pour soutenir le développement \nde cette compétence et \nl’évaluer, car elles savent qu’il ne suffit \npas de mettre les élèves en équipe \npour qu’ils coopèrent dans différentes \ntâches. Un enseignement des attentes \net des comportements à adopter est \nsouhaitable pour soutenir le développement \nde cette compétence. Pour \nbien les déterminer, il faut d’abord se \nquestionner sur le type de tâches coopératives \nà proposer.

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)0.005
metaresearch head score (Gemma)0.010
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.476
Threshold uncertainty score0.947

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0110.006
Scholarly communication0.0110.006
Open science0.0020.009
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0690.015

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 head0.013
GPT teacher head0.225
Teacher spread0.212 · 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
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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