Moderating Role of Perceived Justice in Organizational Citizenship Behavior (Evidence from Iran)
Bibliographic record
Abstract
Background and aim: Satisfaction of employees plays an important role in the quality of their service providing which in turn leads to the promotion of organizational level as well as fulfillment of organization goals and establishment of justice. The perception of justice by employees is one of the factors affecting their satisfaction. In this regard, the present study aims to determine the relationship between social justice and organizational citizenship behavior (OCB) in some job groups of Metro Operation Company in Tehran. The study enjoyed a cross-section-descriptive design which involved 350 employees of selected stations of Metro Operation Company in Tehran. Stratified random sampling method was employed in this study. The data are collected by two researcher-built questionnaires of social justice and organizational citizenship behavior of “Mourman and Blacklee”. Findings: The findings showed that among dimensions of organizational citizenship behavior, civil virtue and courtesy had the highest (3.41) and the least scores 2.91, respectively. Generally, there was a significant association between justice and five dimensions of organizational citizenship behavior (i.e., civic virtue, altruism, courtesy, sportsmanship, and conscientiousness). Regarding the relationship between justice and citizenship behavior and its association with the fulfillment of the organizational goals, it is better to think about the solutions of implementing justice in organization to achieve OCB.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".