Addressing the human resources for health crisis through task-shifting and retention: results from the Africa Health Systems Initiative Support to African Research Partnerships program
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
In 2008, the Global Health Research Initiative (GHRI) invited applications from teams of researchers and decision-makers who were interested in conducting research related to human resources for health and the implementation and use of integrated health information systems in Africa, with special attention to equity considerations. These thematic areas constituted the focus of the Africa Health Systems Initiative - Support to African Research Partnerships (AHSI-RES) program. The Global Health Research Initiative is a partnership of three Canadian agencies: Foreign Affairs, Trade and Development Canada (DFATD), International Development Research Centre (IDRC), and the Canadian Institutes of Health Research (CIHR). GHRI is hosted at IDRC. AHSI-RES was a five year, $5.9 million CDN research program (2008-2013) supported by Foreign Affairs, Trade and Development Canada ($5 million) and the International Development Research Centre ($900 000). AHSI-RES is the research component of the larger DFATD Africa Health Systems Initiative (AHSI) program. The AHSI program is a 10 year, $450-million CDN commitment (2006-2016) to strengthening national-level health strategies and architecture, and is being implemented by Foreign Affairs, Trade and Development Canada. The AHSI-RES program’s purpose is to support policy relevant research, knowledge translation and exchange in the program’s thematic areas. The AHSI-RES program emphasized the importance of ongoing interaction, collaboration, and exchange of ideas between researchers and decision-makers to maximize the likelihood that research findings would be used to inform programs and policies. A decision-maker was defined as ‘an individual who makes decisions about, or influences, health policies or practices.’ The program used different approaches in order to build or increase local capacity for research, knowledge translation, and research use. The long-term objective was: “Health systems research allows African decision makers, policy advocates and health service managers to improve health outcomes and reduce disease burden through more efficient and affordable health systems” [1]. Teams were required to include one African researcher and one African decision-maker, both as co-principal applicants. Other African and non-African researchers and decision-makers could be involved as co-applicants or as collaborators. The co-principal applicants had to be affiliated with an institution located in an AHSI-RES geographic area of focus. Geographic areas of focus included: Francophone West Africa (Mali, Burkina Faso, Benin); Great Lakes and Eastern Africa (Tanzania, Uganda, Kenya); and Southern Africa (Malawi, Mozambique, Zambia).
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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 | 0.036 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.030 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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