An event‐based approach to psychological contracts: The importance of examining everyday broken and fulfilled promises as discrete events
Bibliographic record
Abstract
Summary Psychological contract research has typically focused on employees' perceptions of whether the organization has generally fulfilled or broken its promises/obligations. However, employees can experience broken and fulfilled promises as discrete events on an everyday basis, which may have immediate implications for employees and also influence their generalized psychological contract. Integrating attribution and appraisal theories of emotions, we argue that discrete psychological contract events (i.e., specific instances of a broken or a fulfilled promise) can initiate attribution and appraisal processes that can guide employees' emotional and behavioral responses. Moreover, experiencing a broken versus a fulfilled promise can have distinct implications for employees' outcomes as well as their generalized perceptions of psychological contract fulfillment. Our hypotheses are generally supported using a daily diary study with event sampling. Theoretical contributions include the importance of (a) examining the attribution and appraisal processes underlying everyday discrete psychological contract events, (b) acknowledging distinctions between broken versus fulfilled promises, and (c) understanding how everyday broken/fulfilled promises can influence generalized perceptions of psychological contract fulfillment. Practical contributions include the importance of effectively managing broken and fulfilled promises on an everyday basis and ensuring that employees perceive that the organization does not break and also fulfills its promises.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".