Perceived contract violation and job satisfaction
Bibliographic record
Abstract
Purpose This paper aims to investigate how employees’ perceptions of psychological contract violation or sense of organizational betrayal, might diminish their job satisfaction, as well as how their access to two critical personal resources – emotion regulation skills and work-related self-efficacy – might buffer this negative relationship. Design/methodology/approach Two-wave survey data came from employees of Pakistani-based organizations. Findings Perceived contract violation reduces job satisfaction, but the effect is weaker at higher levels of emotion regulation skills and work-related self-efficacy. Practical implications For organizations, these results show that the frustrations that come with a sense of organizational betrayal can be contained more easily to the extent that their employees can draw from relevant personal resources. Originality/value This investigation provides a more complete understanding of when perceived contract violation will deplete employees’ emotional resources, in the form of feelings of happiness about their job situation. A sense of organizational betrayal is less likely to escalate into reduced job satisfaction when employees can control their negative emotions and feel confident about their work-related competencies.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 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".