The Role of Narcissistic Hypocrisy in the Development of Accounting Estimates
Bibliographic record
Abstract
ABSTRACT In an experiment including experienced managers, we investigate how supervisor and subordinate narcissism influence a supervisor's review of a subordinate's accounting estimate. While narcissistic supervisors express greater liking for narcissistic subordinates (narcissistic tolerance), they nonetheless reject and revise the accounting estimates of narcissistic subordinates to a greater extent than they reject estimates of non‐narcissistic subordinates (narcissistic hypocrisy), even when doing so inhibits the supervisor's ability to reach a profit target. Our findings contribute to extant research in accounting and psychology. We demonstrate that narcissistic hypocrisy extends beyond the evaluation of others and alters narcissists' willingness to rely on other narcissists in a meaningful financial reporting decision. We also find that narcissistic hypocrisy is robust across age, gender, and supervisory experience.
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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 | 0.010 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".