When narcissists exemplify ethics: Contingent consequences of ethical leadership.
Bibliographic record
Abstract
Organizations increasingly encourage, recognize, and reward ethical leadership to preempt the economic and reputational risks associated with ethical failures. At the same time, organizational leadership positions are disproportionately occupied by individuals higher in narcissism. We highlight how the combination of these two phenomena carries important organizational implications by examining how ethical leadership behaviors differentially impact leaders based on their level of narcissism. Building upon self-concordance theory, we introduce a model of contingent consequences of ethical leadership. Our model identifies motivational (i.e., self-efficacy of the leader) and social (i.e., admiration of the leader) mechanisms that explain why ethical leadership positively predicts leadership effectiveness for some leaders, but not for others. We test our model using a field study and two experiments. Findings from these three studies point to a problematic leadership paradox: When leaders higher in narcissism behave more ethically, they incur higher motivational costs and reap fewer social benefits compared to their peers who are lower in narcissism. Results reveal risks to leadership effectiveness for narcissistic leaders who attempt to lead more ethically. We discuss implications for ethical leadership research and practice. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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; both teacher heads agree on what is shown here.
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".