Disentangling the effects of promised and delivered inducements: Relational and transactional contract elements and the mediating role of trust.
Bibliographic record
Abstract
Psychological contracts contain both relational and transactional elements, each of which is associated with unique characteristics. In the present research, the authors drew on these distinct qualities to develop and test hypotheses regarding differential employee reactions to underfulfillment, fulfillment, and overfulfillment of relational and transactional promises. Further, the authors extended their test of the theoretical distinctions between relational and transactional contracts by assessing the relevance of trust as a key underlying mechanism of relational and transactional psychological contract breach effects. Participants in this 3-wave longitudinal study included 342 full-time temporary employees. In support of existing theoretical distinctions, results indicated that employees reacted differently to varying levels of fulfillment of their relational and transactional contracts and that trust is a more central mechanism of relational, as opposed to transactional, psychological contract breach effects. These findings underscore L.S. Lambert, J. R. Edwards, and D. M. Cable's (2003) recent recommendation that the traditional conceptualization and study of psychological contract breach requires expansion.
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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 | 0.010 | 0.065 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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".