Temporal Proximity Matters: The Impact of Justice Information Timing on Psychological Contract Breach Resolution
Bibliographic record
Abstract
Although scholars and practitioners argue that organizations should provide justice information in the aftermath of a psychological contract breach (PC breach) to prevent or reduce violation feelings, it remains unclear whether that information should be provided within a few hours, days, or weeks following a PC breach. We estimated a 2-level time-lagged regression model on experience sampling data from 76 (226 observations), 70 (213 observations), and 70 (344 observations) employees with different intervals to test the durability of informational justice as a moderator on the PC breach-violation feelings relationship. We found that justice information should be provided in close temporal proximity (i.e., within the same day; Study 1) of PC breach to reduce violation feelings. In contrast, neither justice information provided the day (Study 2) or week (Study 3) after a PC breach successfully moderated the PC breach-violation feelings relationship. The current paper underscores the importance of being informationally just in close temporal proximity to a PC breach in line with resolution velocity as an indicator of the effectiveness of the recovery process. We discuss theoretical and practical implications of these findings.
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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 | 0.006 | 0.066 |
| 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 | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".