Promoting Democratization and Good Governance: Rifka Annisa Women Crisis Centre Yogyakarta
Bibliographic record
Abstract
Since the reformation era in 1998, the number of Non-Governmental Organizations in Indonesia is exploding and their impact on Governance growing. Decentralization Policy has supported this trend with its goal to enhance development in the regions, requiring more active involvement of the people in formulating their interests. Organizations can play an important role in the regions as a bridge between the people and the government. In order to strengthen that role, Non-Governmental Organizations must have a solid organisational fundament and political strategies to get actively involved in the policy making process. An additional stronger legal fundament for such an active role could force the government agencies to include NGOs in the part a policy process. This paper delivers a case study on the actual performance of a local Non-Governmental Organization in the field of Gender Politics and Good Governance. Organisational set up and results of attempts to play an active role in articulating the interests of people it represents are reviewed and lead to suggestions for improvement of performance, that can work as guideline for other NGOs in Indonesia who want to contribute to local Governance. Keywords: Civil Society, Good Governance, NGOs, Rifka Annisa Women Crisis Centre
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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 | 0.001 | 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 | 0.009 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.023 | 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".