Traditional Birth Attendants and the Problem of Maternal Mortality in Indonesia
Bibliographic record
Abstract
Since the 1980s, maternal mortality in Indonesia has declined. However, it has always been high by regional standards, and its decline is now stalling. This makes it unlikely that by 2015 Indonesia will have reduced maternal mortality to the level set by the fifth United Nations Millennium Development Goal. In Indonesia, the role of the traditional birth attendant (TBA) in childbirth has been the subject of debate and controversy since colonial times. In efforts to reduce maternal mortality, subsequent health administrations have tried to replace TBAs with modern-trained midwives. Contrary to expectations, however, even in the present era certified midwives have not fully replaced TBAs. Particularly in rural areas, the TBA remains a key actor in birthing care, although now more often in collaboration with the modern midwife. Taking an anthro pological and a historical perspective, the involvement of the TBA in birthing and maternal care, at different times and in different areas of Indonesia, is investigated and, where relevant, compared to that of TBAs in other parts of Southeast Asia. The emergent picture does not support the opinion that the TBA is to blame for high maternal mortality. Poor referral facilities, bad infra structure and insufficient means are the more likely causes. To resolve the maternal mortality problem, governmental health policies should treat the TBA as an ally. How ever, such policies, and promising approaches such as partnerships and village maternity houses, can only be effective when their implementation is adequately backed up by resources.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".