Quels sont les facteurs liés à l’émergence du leadership transformationnel ? Résultats d’une étude empirique
Bibliographic record
Abstract
Très peu d’études ont porté sur les antécédents potentiels du leadership transformationnel, un type de leadership où le gestionnaire considère, stimule et inspire ses collaborateurs afin de catalyser leurs efforts dans la poursuite d’objectifs organisationnels. Cet article présente les résultats d’une étude qui a été réalisée auprès de 157 gestionnaires d’une organisation de sécurité publique et qui cherchait à explorer les antécédents personnels, contextuels et motivationnels du leadership transformationnel. Des corrélations bivariées et des analyses de régression nous ont permis d’identifier que des antécédents liés à la personnalité telle l’extraversion, des caractéristiques motivationnelles telles la vitalité au travail et des caractéristiques du contexte telles un climat d’innovation, ainsi que l’engagement du gestionnaire envers les collègues seraient liés à l’émergence du leadership transformationnel.
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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 | 0.011 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".