Strategic partnerships in the implementation of bonded recycling zones to support circular economy in Banten, Indonesia
Bibliographic record
Abstract
The purpose of this study is to explore the strategic partnerships role of Bonded Recycling Zones (KDUB) in facilitating Indonesia's transition to a circular economy and enhancing sustainable development. Utilizing a qualitative research approach, the study employs in-depth interviews with key stakeholders from various government agencies and the recycling industry, alongside a comprehensive analysis of policy documents. The findings reveal significant opportunities within the KDUB framework, yet also highlight critical gaps in inter-agency coordination, particularly in monitoring and evaluation processes, which are vital for aligning recycling practices with national strategic objectives and environmental standards. The research also underscores the positive impact of fiscal incentives on the recycling sector, while identifying the necessity for more efficient licensing procedures and clearer regulatory guidelines. This study offers original insights into the complexities of policy implementation in the context of circular economy initiatives, providing valuable recommendations for enhancing the effectiveness of KDUB policies and fostering stronger governmental collaboration.
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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 | 0.005 | 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 | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".