Serial mediation of knowledge and commitment to strengthen leadership and green behavior
Bibliographic record
Abstract
Hospitals are one of the health service facilities in Bali Province which contributes to maintaining the balance between social, economic, and environmental to achieve organizational sustainability. Improper and environmentally unfriendly medical waste management, in addition to having a negative impact on the health of living things, can also cause environmental pollution. Finding out how green inclusive leadership affects green behavior is the goal of this study, both directly and through the mediation of environmental knowledge and green commitment. This study targeted hospitals in Bali with a population of 311 and a sample of 175 ER nurses based on proportional random sampling. Data analysis using PLS-SEM method with SmartPLS tool. Green behavior and green inclusive leadership are not associated, according to the test results, but after being mediated by environmental knowledge and green commitment, its influence becomes significant. The results add insight to hospital management to follow up on indicators that are still lacking in improving the green behavior of all hospital personnel in order to achieve organizational sustainability goals.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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".