Bibliographic record
Abstract
Purpose The aim of this study is to know if ethical theories could be connected to some leadership approaches. Design/methodology/approach In the paper eight leadership approaches are selected: directive leadership, self‐leadership, authentic leadership, transactional leadership, shared leadership, charismatic leadership, servant leadership, transformational leadership. Five western ethical theories (philosophical egoism, utilitarianism, Kantianism, ethics of virtue, ethics of responsibility) are analyzed to see to what extent their basic concepts could be connected to one or the other leadership approach. Findings A given ethical theory (such as philosophical egoism) could be suitable to the components of various leadership approaches. Ethical leadership does not imply that a given leadership approach is reflecting only one ethical theory. Rather, ethical leadership implies that for different reasons, various leadership approaches could agree with the same ethical theory. This is what we could call the “moral flexibility of leadership approaches”. Research limitations/implications This study focuses on western ethical theories. A similar study should be undertaken for Eastern ethical theories coming from Buddhism, Hinduism, Confucianism, or Daoism. Practical implications Some dualisms (such as Kantianism‐transformational leadership, philosophical egoism‐transactional leadership) do not reflect the philosophical connections between ethical theories and leadership approaches. Thus, the notion of ethical leadership would have to be redefined. In doing so, the paper reveals how a given ethical theory could be used by different kinds of leaders, and for very different reasons. Originality/value This study will contribute to make ethical theories and ethical leadership more interconnected, in spite of the different (parallel) “conceptual universes” in which they have evolved until now.
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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 | 0.017 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.033 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".