Developing a Model of Compulsory Basic Education Completion acceleration in Support of Millennium Development Goals in Magelang, Indonesia
Bibliographic record
Abstract
This article reports Year One of a two-year study to develop a model to accelerate compulsory basic education completiontoward Millennium Development Goals (MDGs) in Magelang, Indonesia. The study focuses on five issues: (1) profile of MDGs in Magelang, (2) achievement of MDGs, (3) problems in MDGs implementation, (4) model of compulsary basic education completion acceleration, and (5) effectiveness of the model proposed. As R&D undertaking, the data were collected through documentation and interviews with related authorities, including focused group discussion.The initial model underwent a limited test for necessary revision. The findings showed that the Local Government has implemented the compulsary education with relatively high gross and net enrolment rates of 96.80% and low dropouts and repeaters rates. In 2013-2014, many of the students were from outside Magelang. However, such achievements have not complied with MDGs. One possible cause of the problems was a top-down management system, resulting in low participation of the society members. In conclusion, Magelang Municipality has actually been highly committed to the completion of basic education in accordance with the strategic plans 2010-2014 of the National Education Ministry. A team was established to organize relevant activities to accelerate full implementation of the program. Recommended in Year One of the study were that (1) the Local Government’s commitment to education be sustained, (2) the society members’ participation be optimized in data inventories, planning, implementation, monitoring and evaluation of the program, and (3) the optimization of the society’s participation be supported by Local Government, including the stakeholders.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".