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Record W4366816562 · doi:10.37571/2023.0205

Vers une meilleure compréhension de la motivation scolaire chez les élèves de centres de la formation professionnelle : l’importance du rôle du climat relationnel

2023· article· fr· W4366816562 on OpenAlexaffvenueabout
Louise Clément, Alice Levasseur, Caterina Mamprin

Bibliographic record

VenueDidactique · 2023
Typearticle
Languagefr
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsUniversité de MonctonUniversité Laval
Fundersnot available
KeywordsHumanitiesPsychologyPolitical scienceSociologyPhilosophy

Abstract

fetched live from OpenAlex

En prenant appui sur la théorie de l’autodétermination, cette étude examine l’importance du climat relationnel d’après la perception des élèves de centres de la formation professionnelle et de son rôle sur la motivation scolaire de ces derniers. Deux importants facteurs du climat relationnel ont fait l’objet d’une étude plus approfondie, soit la perception de la qualité des relations interpersonnelles (QRI) des élèves envers leurs enseignant·es ainsi que la perception de la confiance et de la méfiance relationnelles des élèves envers leurs enseignant·es. L’échantillon était composé de 908 élèves réparti·es parmi 22 centres de la formation professionnelle du Québec. Les résultats des analyses ont révélé que la confiance et la méfiance relationnelles jouent un rôle médiateur entre la QRI et la motivation des élèves, soulignant le caractère essentiel de relations interpersonnelles de qualité.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.160
Threshold uncertainty score0.318

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.019
GPT teacher head0.293
Teacher spread0.275 · 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 designObservational
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
Published2023
Admission routes3
Has abstractyes

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