Violated contracts, inadequate career support, but still forgiveness: Key organizational factors that determine championing behaviors
Bibliographic record
Abstract
Abstract To establish how and when psychological contract violations steer employees away from championing behaviors, this study addresses the mediating role of beliefs about inadequate career support and the moderating role of forgiveness climates, as perceived by employees. Survey data from 208 employees of a retail organization, along with a simultaneous estimation of mediation and moderation effects (Process macro), reveal that a sense of organizational betrayal undermines efforts to mobilize support for innovative ideas, because employees critique employers for offering limited career support. Perceptions of an organizational climate that forgives mistakes mitigate this harmful process. For championing research, this study unpacks an unexplored link between psychological contract violations and championing efforts, influenced by career‐related adversity and organizational forgiveness. For practitioners, it pinpoints the danger that employees who feel betrayed might inadvertently make things more difficult, because they react with work‐related complacency. Organizations should create benevolent internal environments to diminish this danger.
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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 | 0.003 | 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 | 0.000 | 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) | 0.002 | 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".