Épuisement professionnel des futurs enseignants du primaire : identification des stresseurs et ressources en période de stage
Bibliographic record
Abstract
Épuisement professionnel des futurs enseignants du primaire : identification des stresseurs et ressources en période de stage Formation et profession 33(3), 2025 • ésumé Cet article examine les exigences, ressources et signes d' épuisement professionnel chez 18 futurs enseignants (FE) en stage de dernière année de formation, issus de huit établissements d' études supérieures répartis dans trois régions francophones.L'analyse thématique des entretiens semi-directifs révèle une multiplicité d' exigences et de ressources professionnelles et personnelles, illustrant la complexité de cette étape de formation.Certains témoignages indiquent des signes de fatigue et de l' épuisement professionnel.Ces résultats sont discutés à la lumière du modèle « Job Demands-Resources » et soulignent l'importance d'un encadrement positif et soutenant par leurs maîtres de stage, ainsi que du renforcement des ressources personnelles des FE.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".