Multidimensional Poverty in Indonesia: Trends, Interventions and Lesson Learned
Bibliographic record
Abstract
Despite the Government of Indonesia’s commitment to address human security as stated in its ambitious medium-term development plan and the Millennium Development Goals, poverty in its multidimensionality remain a major issue in Indonesia as a significant proportion of the Indonesian population is still consumption poor. Whilst the number of the poor has been decreasing consistently since 2002, most of those escaping poverty are still vulnerable and just a small shock can send them quickly below the poverty line. Using the PPP $2/day poverty line as a vulnerability measure, the World Bank (2006) found that 45% of Indonesians remain vulnerable to poverty. Nonconsumption poverty is even more problematic which includes malnutrition, maternal health, and access to basic services. For example, a quarter of children below the age of five are malnourished, only about 72% of births are accompanied by skilled birth attendants, 45% of poor households have no access to sanitation, more than half have no access to safe water, and around 20% of children from these households do not continue to junior secondary school.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".