Between a Rock and Hard Place: Combined Effects of Authentic Leadership, Organizational Identification, and Team Prototypicality on Managerial Prohibitive Voice
Bibliographic record
Abstract
Managers are installed by the organization's stakeholders and shareholders to increase the organization's value; at the same time, they depend on their subordinates' acceptance to fulfill this leadership role. If the interest of the organization collides with the interest of their team, some managers act in the interest of their followers accepting potential disadvantages for their organizations and/or external stakeholders. In two experimental studies comprised mainly of German (N = 111) and US (N = 323) managers, we examined combined effects of authentic leadership, organizational identification, and self-perceived team prototypicality on managerial integrity operationalized as expressing work-related concerns to prevent organizations from harm (i.e., managerial voice). Our results show direct effects of authentic leadership and organizational identification on voice behavior across both studies. Furthermore, organizational identification increased voice for managers' low in authentic leadership pointing at a compensation effect. Finally, leader team prototypicality decreased the effect of identification on voice for managers high in authentic leadership but increased voice for managers low in authentic leadership, but only if these managers identified with their organization. In sum, our findings complement prior research that focused mainly on safety and instrumentality concerns by emphasizing the relevance of self-related antecedents of managerial voice.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".