Build the cradle later: An examination of perinatal care and mortality in village nepal.
Bibliographic record
Abstract
Background: As perinatal and neonatal mortality move to the foreground of the debate on how best to improve child survival in poor countries, there appears a pressing need to test potential interventions. Implicit in testing is the ability to document birth and neonatal outcomes in rural communities. The thesis sets perinatal events in the context of the child survival literature and critically examines current knowledge about practices, outcomes and interventions. This knowledge is found to be limited, particularly in terms of practices and outcomes in rural settings in developing countries. Methods: Two methods are described to document perinatal events in villages in Makwanpur district, Nepal. (1) a census of women of reproductive age, collecting information about previous pregnancies and most recent live births (2) a prospective system of registration that tracked women through childbirth and infants through the neonatal period. Both methods yielded information on pregnancies, birth outcomes, care practices and health care seeking patterns. Results: The census collected information from 12,170 women, of whom 4867 had given birth in the preceding two years. The prospective surveillance collected information on 3522 pregnancies over two years. The thesis presents results under two broad themes: (1) a description of the birth experience of women in rural Makwanpur, its outcomes, practices and care seeking patterns (2) a comparison of the two methods of data collection. Poverty was the norm in rural Makwanpur and only a quarter of participants were literate. 30% of pregnant women had any antenatal care, which tended to be both late and limited, and 95% gave birth at home. Three percent of women were helped by trained health workers and there were compromises in hygiene and warmth at the time of delivery. Breastfeeding rates were high. The prospective registration process suggested a neonatal mortality rate of 37 per thousand live births, a figure higher than that from the census (27 per thousand), and thus higher than would be estimated by existing methodologies. Discussion: Antenatal, delivery, postnatal and neonatal care practices and care seeking are compared with existing knowledge from other studies. Their implications for programmatic intervention are considered. The issue of recall-based data collection is discussed as it bears upon the evaluation of public health interventions. The feasibility of registration systems is assessed and recommendations made for increasing reliability, expansion and replication, and reducing system costs. 386 words.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".