Improving pregnancy outcomes in low- and middle-income countries
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it