Reawakening perceived person organization fit and perceived person job fit: Removing obstacles organizational commitment
Bibliographic record
Abstract
This study aimed to examine and analyze the effect of Perceived Person Organization Fit and Perceived Person Job Fit on Organizational Citizenship Behavior with Organizational Commitment as an intervening variable. This research was conducted using a descriptive method in the Social Welfare Institution at Central Aceh -Takengon with sample of 42 respondents. The approach used in this research was Structural Equation Model (SEM) with Partial Least Square (PLS) analysis tool 3.0. The results showed that the Perceived Person Organization Fit (P-O Fit) and Perceived Person-Job Fit (P-J Fit) had a significant positive effect on Organizational Commitment. Perceived Person Organization Fit (P-O Fit) and Perceived Person-Job Fit (P-J Fit) had a significant positive effect on Organizational Citizenship Behavior (OCB). Organizational Commitment had a significant positive effect on Organizational Citizenship Behavior (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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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 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".