Improving pregnancy outcomes in low- and middle-income countries
Bibliographic record
Abstract
This paper reviews the very large discrepancies in pregnancy outcomes between high, low and middle-income countries and then presents the medical causes of maternal mortality, stillbirth and neonatal mortality in low-and middle-income countries. Next, we explore the medical interventions that were associated with the very rapid and very large declines in maternal, fetal and neonatal mortality rates in the last eight decades in high-income countries. The medical interventions likely to achieve similar declines in pregnancy-related mortality in low-income countries are considered. Finally, the quality of providers and the data to be collected necessary to achieve these reductions are discussed. It is emphasized that single interventions are unlikely to achieve important reductions in pregnancy-related mortality. Instead, improving the overall quality of pregnancy-related care across the health-care system will be necessary. The conditions that cause maternal mortality also cause stillbirths and neonatal deaths. Focusing on all three mortalities together is likely to have a larger impact than focusing on one of the mortalities alone.
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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 | 0.007 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.009 | 0.017 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".