Gender dan Tingkat kepedulian Masyarakat terhadap Sampah
Bibliographic record
Abstract
Indonesia is the second largest producer of plastic waste in the world after China, one source of waste is from the tourism sector such as in the Borobudur Temple Area, Central Java. The problem of low awareness and gender norms that are still closely embedded in Indonesian society are inhibiting factors in modern approaches to waste management, thereby impacting the burden on local governments in waste management. The aim of this study was to determine the effect of gender on concern for waste. Methods: Cross-sectional deskriptif survey study in the Borobudur sub-district area of 374 respondents representing the X generation or millennial generation and Z generation. This study shows that the difference in the average value (mean) of the variabels of knowledge, concern, perception, millennial PKK actions, and external faktors regarding institutions is slightly higher in the female group, namely 0.5005, 0.2207, 0.1452, 0 .8338, and 0.1046. But, individual perceptions of concern for community groups are slightly higher in the male group, namely 0.0659. This study shows that concern for waste, the female group's average value of each variable is slightly higher than the male group, and only one variable, namely external factors, individual perceptions of concern for community groups is slightly lower.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".