Auto-effi cacité émotionnelle et épuisement professionnel de directions d'établissement d'enseignement
Bibliographic record
Abstract
Cette etude evalue le role de l’auto-effi cacite emotionnelle (AEE) sur les symptomes de l’epuisement professionnel (EP). Trois hypotheses sont verifi ees en lien avec des etudes anterieures, soit que l’AEE est negativement liee a l’epuisement emotionnel, a la perte d’accomplissement personnel au travail et a la depersonnalisation. Les 406 participants dirigent des etablissements d’enseignement de la province de Quebec au Canada. L’echelle d’AEE (α = ,92) de Deschenes, Dussault, & Fernet (2011) et le MBI-GS de Schaufeli, Leiter, Maslach, & Jackson (1996) (epuisement emotionnel : α = ,91, depersonnalisation : α = ,78 et perte d’accomplissement personnel : α = ,87) ont ete utilises pour mesurer les construits a l’etude. Le modele verifi e comprend sept indicateurs pour le facteur de l’AEE et deux indicateurs pour chaque symptome de l’epuisement professionnel. Il presente de bonnes statistiques d’ajustement du modele aux donnees qui confi rment les hypotheses : χ2 = 113,61, p < ,001, χ2/dl = 1,93, NNFI = ,97, CFI = ,98 et RMSEA = ,05.
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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 | 0.008 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.025 | 0.006 |
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".