You're draining me! When politically inept employees view organization-linked emotional exhaustion and unforgiveness as reasons for diminished job performance
Bibliographic record
Abstract
Purpose This study seeks to unpack the negative relationship between employees' political ineptness and their job performance, by proposing a mediating role of organization-induced emotional exhaustion and a moderating role of perceived organizational unforgiveness. Design/methodology/approach The research hypotheses were tested with three-round survey data collected among employees and their supervisors across multiple industry sectors. Findings Political ineptness diminishes the likelihood that employees undertake performance-enhancing work behaviors because they perceive that their employer is draining their emotional resources. This mediating role of organization-induced emotional exhaustion is particularly salient when they perceive that organizational authorities do not forgive mistakes. Practical implications This study reveals a critical risk for employees who find it difficult to exert influence on others: They become complacent in their job duties, which then might further compromise their ability to leave a positive impression on others. This counterproductive process is especially prominent if organizational leaders appear unforgiving. Originality/value This study contributes to extant research by explicating an unexplored mechanism (organization-induced emotional exhaustion) and catalyst (organizational unforgiveness) related to the escalation of political ineptness into diminished job performance.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".