Indonesia’s Water Diplomacy and Leadership in Achieving SDG 6: A Strategic Approach to Sustainable Development
Bibliographic record
Abstract
Indonesia has contributed significantly in the effort to achieve Sustainable Development Goal 6 (SDG 6) through domestic water management and by advocating for global water diplomacy. At the domestic level, Indonesia created programs such as PAMSIMAS and the 100-0-100, which have expanded access to clean water and sanitation. However, some challenges persist, such as regional gaps, water pollution, and climate change weaknesses. At the global level, Indonesia influences platforms like the UN Water Conference and ASEAN to support fair water management and sustainable solutions. The appointment of Indonesia’s former foreign minister, Retno Marsudi, as the UN Special Envoy for Water Issues will provide Indonesia with more opportunities to impact the issue of global water regime, as this will connect international agendas with Indonesia’s national priorities. This study will explore Indonesia's dual approach opportunities to support domestic reforms with global commitments. This will be conducted through emphasizing accomplishments and challenges, as well as strengthening its role as a leader in sustainable development.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".