Citizenship behaviors against organizational interests: perceived follower support and supervisor competence uncertainty
Bibliographic record
Abstract
Purpose Adopting a followership perspective and drawing upon the literature on perceived support, we provide new theoretical insights into when and why supervisors engage in unethical behavior with the intention of benefiting a “favorite” follower, referred to as unethical favoritism behavior (UFB). Design/methodology/approach We conducted two studies: an experiment and a multi-rater field study. Data were collected and analyzed using AMOS and the Macro process for SPSS. Findings We found that a follower’s standing among his or her peers in terms of citizenship behaviors toward their supervisor (i.e. relative organizational citizenship behaviors toward supervisor or ROCBS) has a positive effect on the supervisor’s perception of the follower’s support. The results further reveal that the choice of the supervisor on whether to reciprocate or not the perceived support (triggered by ROCBS) with UFB depends on the supervisor’s competence uncertainty (i.e. the degree of supervisor uncertainty regarding his/her work competencies). Originality/value Our findings broaden the way the supervisor–follower relationship has traditionally been investigated in the organizational behavior literature by showing that under certain circumstances, followers’ good behaviors might become an antecedent to supervisors’ unethical acts.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".