Combatting Environmental Crisis: Green Orientation in the Sri Lanka Navy
Bibliographic record
Abstract
The military’s ongoing efforts to protect the environment are clearly visible. The aim of this study is to bridge an empirical gap, i.e., there is no mediating effect of employee engagement on the relationship between green orientation and employee job performance in the Sri Lanka military context. Employee engagement is the employee’s head, heart and hand involvement in their job as well as their organization. Employee job performance is a main consequence of employee engagement. Because of this consequence, employee engagement has grabbed attention in both the business context and the military context. This quantitative study was achieved through objectives, namely, to identify the impact of green orientation on employee engagement, to identify the impact of employee engagement on employee job performance, and to identify the mediating effect of employee engagement on the relationship between green orientation and employee job performance. The unit of analysis is individual, i.e., officers in the Sri Lanka Navy. The sample size is 243. A cross-sectional study was done in a non-contrived environment with minimum researcher interference. Findings of this study suggest the direct relationship of green orientation and employee engagement, as well as the mediation effect of employee engagement on this relationship.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 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".