Justice, jealousy and performance: Evidence from neo-feudal Pakistan
Bibliographic record
Abstract
Although jealousy is one of the most frequent emotions felt by employees at workplace with far-reaching consequences, empirical research understanding this discrete emotion remains scant, especially in frontline services. Drawing on justice theory, this research investigates the unexplored mediating role of workplace jealousy in the relationship between perceived injustice and a key frontline employee outcome, job performance, in service-setting in Pakistan. The moderating role of employee self-efficacy is also examined in the jealousy – performance relationship. Multi-source and multi-level data collected across two studies in frontline settings demonstrate that, as an outcome of perceived injustice, jealously can be deleterious for frontline performance. The study further offers useful insights into regulating jealousy at workplace by demonstrating that self-efficacy attenuates the deleterious effect of jealousy on frontline 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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".