The Relationship Between the Adiwiyata Program Based on Environmental Activities and Students' Environmental Care Attitudes in Supporting Green Schools
Bibliographic record
Abstract
The Adiwiyata program based on environmental activity is a strategic step in fostering students' environmentally caring attitudes that support sustainable Green Schools.This study aims to determine the relationship between the Adiwiyata program based on environmental activity and the character value of environmental care at SD Negeri 1 Sawojajar, Malang, Indonesia.This research uses a correlational method with a quantitative approach.The population of this study consists of 75 students from grades III, IV, and V at SDN 1 Sawojajar.Data collection was conducted through questionnaires, documentation, and observations measuring students' environmental care attitudes.Data analysis used correlation with a significance level of <0.05.Based on the results of the analysis, it was found that there was a significant relationship between the Adiwiyata program based on environmental activities and students' environmental care attitudes, this was shown by the results of the hypothesis test which was greater (r=0.435) with a significance level of 0.005.The environmental activity-based Adiwiyata program actively engages students in environmental management activities, thereby strengthening their environmental care attitudes and supporting the creation of an environmentally friendly and sustainable green school.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".