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Record W7163525331 · doi:10.5281/zenodo.17524235

BESOINS PSYCHOLOGIQUES FONDAMENTAUX DE STAGIAIRES EN ENSEIGNEMENT AU SECONDAIRE EN EMPLOI: PERCEPTIONS DES PRATIQUES D'ACCOMPAGNEMENT EM STAGE

2025· article· en· W7163525331 on OpenAlexaffabout
Josée-Anne Gouin, Matthieu Petit, Jean-Christophe Potvin, Abire Ismaili

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicCareer Development and Diversity
Canadian institutionsUniversité de SherbrookeUniversité Laval
Fundersnot available
KeywordsProfessional developmentFace (sociological concept)Continuing educationGraduate students

Abstract

fetched live from OpenAlex

Au Québec, face à la pénurie de personnel enseignant, de plus en plus d’étudiants en enseignement se font offrir des stages en emploi avant d’avoir complété leur baccalauréat. L’accompagnement de ces personnes diffère puisqu’elles n’enseignent pas aux élèves d’un enseignant associé. Les stagiaires en emploi ont l’entière responsabilité de groupes d’élèves, avec tous les défis que cela représente. L’objectif de notre étude est de mieux comprendre les pratiques d’accompagnement perçues par ces stagiaires lors d’un tel stage. Guidés par la théorie de l’autodétermination (Ryan et Deci, 2020), des entretiens semi-dirigés ont été réalisés auprès de quatre stagiaires notamment en ce qui a trait à la satisfaction de leurs besoins d’autonomie, de compétence et d’appartenance. Nos résultats montrent que ces stagiaires vivent une insertion professionnelle à grande vitesse durant laquelle les tâches confiées peuvent s’avérer exigeantes et qu’un accompagnement mieux adapté semble souhaitable.

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)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.733
Threshold uncertainty score0.537

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.005
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.035
GPT teacher head0.311
Teacher spread0.276 · 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 designQualitative
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
Published2025
Admission routes2
Has abstractyes

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