Bibliographic record
Abstract
Purpose – The purpose of this paper was to examine the mediating role of psychological contract (PC) violation on the relationship between perceived organizational support (POS) and a set of work-related affects (trust), attitudes (job satisfaction, commitment to the organization and intention to leave) and individual effectiveness (civic virtue). Design/methodology/approach – Two independent studies were conducted (N= 162 andN= 242). To test the mediating effect, the procedure of Baron and Kenny (1986) was used in both studies. Findings – Overall, in both studies, data reported the same pattern. While PC violation played a partial mediating role between POS and affect (i.e. trust in organization) and attitudes (i.e. commitment, satisfaction and intention to leave), PC violation failed to mediate the relationship between POS and individual effectiveness (i.e. civic virtue). Practical implications – The results suggest that the implementation of supportive actions may help employees overcome frustrations tied to their perception that the PC has been broken. Originality/value – This study contributes to PC literature. Given that violation was less examined than breach, this paper contributes to greater understanding by addressing the relationship between violation, POS and a set of work outcomes.
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 | 0.003 | 0.017 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".