Analisis Kebijakan Pengelolaan dan Budidaya Ekosistem Gambut di Indonesia: Penerapan Pendekatan Advocacy Coalition Framework
Bibliographic record
Abstract
Indonesia has become the fourth largest owner of peat reserves in the worldafter Canada, Russia and the United States. Peatlands play a major role ascarbon sinks and maintain a hydrological system. The destructive andoxidized characteristics of peat make the International and IndonesianGovernments pay high attention to the management and protection of peatecosystems. Through the Advocacy Coalition Framework (ACF) approach,this study found that there are a variety of actors and stakeholders whoinfluence the dynamics of peat management and cultivation policyformulation in Indonesia. The actors and stakeholders formed a coalition bycarrying out the logic of their respective belief systems, namely: Coalition Awhich has a belief system that peat land is a potential resource developed forcultivation and Coalition B which has a belief system that views peatecosystems as vulnerable ecosystems that must be protected and rehabilitated.The results of this study are expected to be able to provide recommendationsneeded in realizing sustainable management of peat ecosystems.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".