Armed conflicts and national trends in reproductive, maternal, newborn and child health in sub-Saharan Africa: what can national health surveys tell us?
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
Armed conflicts are widespread in sub-Saharan Africa and considered to be an important factor in slowing down national progress in reproductive, maternal, newborn and child health (RMNCH). The measurement of the impact of conflicts on national levels and trends in RMNCH is difficult. National surveys conducted before and sometimes during and after conflicts are a major source of information on the national and local effects of conflicts on RMNCH. We examined data from national surveys in 13 countries in sub-Saharan Africa with major conflicts during 1990-2016 to assess the levels and trends in RMNCH intervention coverage, nutritional status and mortality in children under 5 years in comparison with subregional trends. The surveys provide substantive evidence of a negative association between levels and trends in national indicators of RMNCH service coverage, child growth and under-5 mortality with armed conflict, with some notable exceptions. National surveys are an important source of data to assess the longer term national consequences of conflicts for RMNCH in most countries, despite limitations due to sampling and timing of the surveys.
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 | 0.017 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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