EVIPNet Africa's first series of policy briefs to support evidence-informed policymaking
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
EVIPNet (Evidence-Informed Policy Network) Africa—a network of World Health Organization (WHO)-sponsored knowledge-translation (KT) platforms in seven sub-Saharan African countries—was launched at a meeting in Brazzaville, Congo, in March 2006 (1;2). EVIPNet Africa can trace its origins to resolutions from both the Ministerial Summit on Health Research (November 2004) and the World Health Assembly (May 2005) (10;11), the spirit of which was re-affirmed at the Global Ministerial Forum on Research for Health (November 2008) (13). The World Health Assembly called for “establishing or strengthening mechanisms to transfer knowledge in support of evidence-based public health and health care delivery systems and evidence-based related policies” (10). EVIPNet Africa can trace its inspiration to a more local development: the preparatory work that led to the establishment of the East African Community–sponsored Regional East African Community Health (REACH) Policy initiative, a KT platform involving Kenya, Tanzania, and Uganda (and more recently Burundi and Rwanda as well). REACH Policy is now part of the EVIPNet Africa family.
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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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