An Explorative Inquiry on Educational Decentralisation in Bantul District, Jogjakarta, Indonesia
Bibliographic record
Abstract
For a prolonged period of time, Indonesia implemented a centralised education system which was characterised by the dominant role of the Ministry of National Education in making education policy. In 1999, Indonesia introduced two decentralisation laws: (a) Law No.22/1999 on regional government; and (b) Law No.25/1999 on fiscal balance between the central government and the local governments. These laws devolves central government authority and responsibilities to local governments in all fields except foreign policy, defense and security, justice, monetary, debt, fiscal matters, and religious affairs, including in education sector. This study provides an analysis of the implementation of educational decentralization based on in-depth interviews with a sample of 27 purposively selected participants. This study presents three themes in which educational decentralisation are conducted: education management, curriculum development, and stakeholders’ participation. Interviews results suggest that local government now has more authority and responsibility over education which enables the determination and implementation of education policies relevant to local need. It is however, the Central Government through the Ministry of Education (MONE) still retains a large portion of authority and responsibility for educational curriculum. Evaluation on participation of educational stakeholders indicates that the education stakeholders had played a significant role in education following decentralisation.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".