The Politics of Universal Free Basic Education in Decentralized Indonesia: Insights from Yogyakarta
Bibliographic record
Abstract
Since the fall of Suharto's New Order, Indonesia's central government has substantially strengthened the legal and financial basis of universal free basic education (UFBE). Yet sub-national governments have varied considerably in their responses to the issue, with some supporting UFBE and others not. Why has this happened? What are the implications for the future of UFBE in Indonesia? And what does Indonesia's sub-national experience tell us about the political preconditions for UFBE in developing countries? We try to shed some light on these questions by examining the politics of UFBE in Bantul and Sleman, two districts in the Special Region of Yogyakarta. We argue (1) that these districts' different responses to UFBE have reflected the extent to which their bupati have pursued populist strategies for mobilizing votes at election time and there has been resistance to UFBE from groups such as business, the middle classes and teachers; (2) that Indonesia's sub-national experience suggests that there is an alternative pathway to UFBE besides organization of the poor by political entrepreneurs; and (3) that the future of UFBE in Indonesia thus rests on the nature of bupatis' strategies for advancing their careers and the strength of local groups opposed to UFBE.
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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 | 0.006 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".