The Effects of Employee Engagement and Productivity Mediate Transformational Leadership and OCB on Bawaslu Commissioners' Performance
Bibliographic record
Abstract
This quantitative study is aimed to know the effects of each variable, those are Performance as dependent, Transformational Leadership and OCB as independent and Employee Engagement and Productivity as intervening variables by using Slovin formula to determine respondents, and those are 65 commissioners of Bawaslu of all Districts and Cities in East Jawa, in category of nonprobability sampling by using purposive sampling technique. In collecting data, it used questionnaire by using primer data and four-points Likert-scale ranging. The results of this study are, some of them are in accordance with the hypothesis that is having significant effects, while the other some are not significant between Employee Engagement on the performance. This affects to mediating result, so Employee Engagement variable has no significant effects. While, transformational leadership variable does not affect significantly on Bawaslu commissioners’ performance through Employee Engagement and Organizational Citizenship Behavior (OCB) does not have effects significantly on Bawaslu commissioners’ performance through Employee Engagement.
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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 | 0.002 | 0.005 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".