Uptake and impact of research for evidence-based practice: lessons from the Africa Health Systems Initiative Support to African Research Partnerships
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. GHRI 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). It is hosted at IDRC.
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.
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 | 0.674 | 0.677 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.012 | 0.041 |
| Scholarly communication | 0.047 | 0.060 |
| Open science | 0.011 | 0.059 |
| Research integrity | 0.021 | 0.026 |
| Insufficient payload (model declined to judge) | 0.010 | 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".