Do promises matter? An exploration of the role of promises in psychological contract breach.
Bibliographic record
Abstract
Promises are positioned centrally in the study of psychological contract breach and are argued to distinguish psychological contracts from related constructs, such as employee expectations. However, because the effects of promises and delivered inducements are confounded in most research, the role of promises in perceptions of, and reactions to, breach remains unclear. If promises are not an important determinant of employee perceptions, emotions, and behavioral intentions, this would suggest that the psychological contract breach construct might lack utility. To assess the unique role of promises, the authors manipulated promises and delivered inducements separately in hypothetical scenarios in Studies 1 (558 undergraduates) and 2 (441 employees), and they measured them separately (longitudinally) in Study 3 (383 employees). The authors' results indicate that breach perceptions do not represent a discrepancy between what employees believe they were promised and were given. In fact, breach perceptions can exist in the absence of promises. Further, promises play a negligible role in predicting feelings of violation and behavioral intentions. Contrary to the extant literature, the authors' findings suggest that promises may matter little; employees are concerned primarily with what the organization delivers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.014 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.003 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".