Asking different questions: A call to action for research to improve the quality of care for every woman, every child
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
Despite decades of considerable economic investment in improving the health of families and newborns world-wide, aspirations for maternal and newborn health have yet to be attained in many regions. The global turn toward recognizing the importance of positive experiences of pregnancy, intrapartum and postnatal care, and care in the first weeks of life, while continuing to work to minimize adverse outcomes, signals a critical change in the maternal and newborn health care conversation and research prioritization. This paper presents "different research questions" drawing on evidence presented in the 2014 Lancet Series on Midwifery and a research prioritization study conducted with the World Health Organization. The results indicated that future research investment in maternal and newborn health should be on "right care," which is quality care that is tailored to individuals, weighs benefits and harms, is person-centered, works across the whole continuum of care, advances equity, and is informed by evidence, including cost-effectiveness. Three inter-related research themes were identified: examination and implementation of models of care that enhance both well-being and safety; investigating and optimizing physiological, psychological, and social processes in pregnancy, childbirth, and the postnatal period; and development and validation of outcome measures that capture short and longer term well-being. New, transformative research approaches should account for the underlying social and political-economic mechanisms that enhance or constrain the well-being of women, newborns, families, and societies. Investment in research capacity and capability building across all settings is critical, but especially in those countries that bear the greatest burden of poor outcomes. We believe this call to action for investment in the three research priorities identified in this paper has the potential to achieve these benefits and to realize the ambitions of Sustainable Development Goal Three of good health and well-being for all.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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