Education for safe motherhood: a Save the Mothers' advocacy initiative
Bibliographic record
Abstract
Purpose The provision of and access to healthcare for pregnant women is a complicated labyrinth of social and health‐related issues. The purpose of this paper is to discuss a new approach by the Save the Mothers organization to stimulate changes leading to safer and healthier pregnancies for Ugandan women using a Master of Public Health Leadership (MPHL) as the mechanism for education, advocacy, and network development. Design/methodology/approach Save the Mothers developed and supports a modular, post‐graduate, multi‐disciplinary MPHL. This training is designed to develop public health leaders who create transformative local projects and networks of professionals advocating for safe motherhood and consequent decreased child mortality. Findings Students and graduates have begun to change the conditions in Uganda for women and children by promoting safe motherhood practices and policies. Examples include a journalist, a politician, a social worker, and a school principal who have brought the issues into their spheres of influence and practice. Measurement of the impact of this approach is ongoing. Practical implications This program provides a locally based, culturally appropriate approach to change, which could be adapted to a variety of other locales and development issues. This program permits practicing professionals to remain employed while undertaking advanced training, establishes the implementation of local projects, and links a graduate university program with diverse community leaders. Originality/value This unique approach within Africa may be a model for the development of multidisciplinary, education‐based initiatives to change conditions in developing countries using existing expertise and stimulating effective advancement through safe motherhood networks.
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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 | 0.012 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".