Bibliographic record
Abstract
Abstract This paper reviews two major ethical theories and the manner in which the values they espouse are associated with the directive, transactional, and transformational leadership styles. A model of ethical leadership is proposed which relates the dimensions of these styles to the level of the leader's moral development. Transformational leadership appears to be most closely connected to deontology, while transactional leadership would seem to be related more to teleological ethics, and directive leadership to ethical egoism, a category of teleology. The paper concludes with some suggestions for future research. Résumé Cette étude passe en revue deux théories principales d'éthiques et la façon dont les valeurs qu'elles compren‐nent sont liées aux styles de leadership directif, transac‐tionnel, et transformationnel. L'auteur présente un mo‐dèle de leadership éthique dans lequel les dimensions de ces styles sont associées au niveau de développement moral du leader. Le leadership transformationnel semble être lié plus étroitement à la déontologie tandis que le leadership transactionnel serait associé plutôt à l'éthique téléologique et le leadership directif à l'égo‐ïsnie éthique, une catégorie de la téléologie. L'étude se termine par quelques suggestions de recherches ultérieures.
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 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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".