Relationship Clean-Up Time: Using Meta-Analysis and Path Analysis to Clarify Relationships Among Job Satisfaction, Perceived Fairness, and Citizenship Behaviors †
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Although perceived fairness and job satisfaction predict organizational citizenship behaviors (OCB), researchers have pondered the conceptual relationships among these constructs. Using path analysis on meta-analytically derived coefficients, the authors compared four models: full mediation (job satisfaction mediates fairness-OCB relationships), partial mediation, independent effects, and a spurious effects model (the job satisfaction—OCB relationship is spurious because perceived fairness is a common cause). The authors found greatest support for the independent effects model: Job satisfaction and different types of perceived fairness accounted for unique variance in OCB dimensions. The article discusses implications for research and practice, and offers suggestions to advance theory in this area.
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.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it