Indonesia's Sustainable Development Goals Resolving Waste Problem: Informal to Formal Policy
Bibliographic record
Abstract
Indonesia declares itself as a country-oriented towards sustainable development. However, sustainable development goals are not clearly realized in every government policy, particularly on the environmental issue. This problem invites the important question of how Indonesia realizes or constructs public policy regarding waste problems. This paper aims to examine Indonesian public policies, both initiated by the community (informal policy) and government programs (formal policy). Based on the review of the amount of data and literature, this paper finds two arguments. First, the objectives of sustainable development are substantially stated in the Indonesian regulations. This legal policy is a government action in fulfilling citizens' rights regarding the good environment as guaranteed in the Constitution of the Republic of Indonesia. However, this formal policy has not been implemented proportionally. Second, the inefficiency of formal policy is actually patched by informal policies such as policy on personal drinking bottles, policy on the use of organic packing and shopping bags, etc. Nevertheless, in reality, the waste problem in Indonesia is far from what have been expected and still requires more sophisticated solutions both in the formal and informal sectors.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".