Quiet Workaholics? The Link Between Workaholism and Employee Silence and Moral Voice as Explained by the Social‐Cognitive Theory of Morality
Bibliographic record
Abstract
ABSTRACT When employees engage in potentially harmful behavior, organizations and societies rely on others to voice these issues. We propose that workaholism, a way that some individuals develop to deal with and thrive in today's intense and demanding work environment, reduces these individuals' intention to engage in moral voice and increases employee silence. Drawing on social‐cognitive theory of morality, we propose that this occurs because workaholism, being driven by an inner compulsion to working extensively, disengages moral self‐regulation which, in turn, affects both the activation of moral behavior (i.e., voice intentions) and the inhibition of immoral behavior (i.e., employee silence). Further, based on social‐cognitive theory's premise that moral behavior is jointly regulated by personal and social standards, we propose that a context that endorses this inner pressure to work (i.e., climate of self‐interest) strengthens the relationship between workaholism and moral disengagement. Findings from two three‐wave time‐lagged studies of Italian and UK employees suggest that workaholism—but not workload—is associated with moral disengagement and indirectly with more silence and less moral voice intention. Additionally, Study 2's moderated‐mediation model showed that perceived climate of self‐interest moderates the relationship between workaholism and moral disengagement and revealed dimension‐specific effects of workaholism.
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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 | 0.011 |
| 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 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".