Capital psychologique et bien-être PERMA des enseignants de Fédération Wallonie-Bruxelles : une aide à la réflexion autour du développement du bien-être des enseignants
Bibliographic record
Abstract
Capital psychologique et bien-être PERMA des enseignants de Fédération Wallonie-Bruxelles : une aide à la réflexion autour du développement du bien-être des enseignants Formation et profession 32(2) 2024 • ésumé Une enquête a été soumise à des enseignants de Fédération Wallonie-Bruxelles (N=143) en décembre 2021 pour mesurer leur niveau de bienêtre grâce au modèle PERMA de Seligman (2012), (y compris émotions positives, engagement, relations positives, sens et accomplissement) ainsi que leur niveau de ressources psychologiques, grâce au modèle de capital psychologique (PsyCap), comprenant l' espoir, l'auto-efficacité, l' optimisme et la résilience (Luthans & Youssef, 2004).Les résultats montrent que les deux modèles sont bien liés.De plus, un profil des enseignants est esquissé, marqué par un fort sentiment d'auto-efficacité, d' espoir, de sens et d' engagement, face à un optimisme et un sentiment d'accomplissement faibles.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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".