The Influence Of Ethical Leadership On Managerial Performance: Mediating Effects Of Mindfulness And Corporate Social Responsibility
Bibliographic record
Abstract
In a continuing world of corporate misdeeds and unscrupulous decision making, much of the management and academic literatures points to the incomplete knowledge of the consequences of ethics leadership. One of the bastions of ethics gatekeeping in the firm is the CFO but remarkably scant information can be found on their perceptions concerning ethics leadership. This study addresses this void by examining mindfulness and corporate social responsibility (CSR) initiatives as new mediating linkages in comprehending the influence of ethics leadership on managerial performance. Findings reveal that ethical leadership is positively associated with CSR initiatives which, in turn, operate to enhance managerial performance. Simultaneously, ethical leadership manifests a significant positive relationship with mindfulness but, surprisingly, there is no corresponding relationship with managerial performance. Instead, mindfulness indirectly influences managerial performance through the intervening effects on CSR initiatives. These findings suggest that firms can acquire better managerial performance by focusing efforts on CSR strategies, bringing cognitive processes of mindfulness to bear on these actions, and grooming ethics leadership. In addition, the results offer researchers new relationships to model in the leadership domain.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".