Whistleblowing in family firms: power and justice dynamics
Bibliographic record
Abstract
Abstract We explore how power and justice dynamics influence whistleblowing behaviour in family firms, focusing on the under-explored construct of connection power. Power and justice are two important, interrelated forces strongly affecting moral behaviour. We hypothesise a moderated moderation model and use a 2 × 2x2 between-subject experiment with 331 participants to test our conceptual model. We find that the family relation (i.e., connection power) of the wrongdoer changes what we know about the relationship between the legitimate power of the observer and whistleblowing likelihood, and that, in some instances, observers with high legitimate power are even less likely to blow the whistle than those with low legitimate power. Our exploration further reveals that, although the family relation of the wrongdoer discourages would-be whistleblowers, even those with legitimate power, organisational justice consistently increases the likelihood of whistleblowing in every case.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 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".