Training Multidisciplinary Leaders for Health Promotion in Developing 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
The global picture of maternal mortality and morbidity has changed very little over the past 20 years despite isolated (and often medically based) efforts to improve the situation. A multidisciplinary approach to this very complicated social and cultural problem has been recommended. This article describes the approach taken by the Save the Mothers program in Uganda (Master of Public Health Leadership) and its focus on training national, primarily nonmedical, advocates to bring about the political and cultural change needed to improve maternal health. Emphasis is placed on attracting the right students (through targeted advertising and interviews of candidates), delivering the appropriate package of information to these multidisciplinary students (through problem-based learning and experiential opportunities in the community), and fostering networks among students and graduates to keep the issue of maternal mortality high on their personal and political agendas. Students benefit from a flexible program that allows them to continue to work and study simultaneously while ensuring a high-quality program with faculty who are experts in their area of teaching. Students require practical assistance in their research endeavors and are encouraged to focus their topic on a field related to their place of employment.
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 | 0.004 | 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 | 0.001 |
| 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