ANALYSING THE IMPACT OF THE AFRICAN FORUM FOR RESEARCH AND EDUCATION IN HEALTH (AFREHEALTH) IN GHANA: A QUALITATIVE EVALUATION STUDY
Bibliographic record
Abstract
To evaluate the impact of the African Forum for Research and Education in Health (AFREhealth) in Ghana in its first five years, after its launch in 2016. AFREhealth is an African initiative created and implemented by Africans in their continent with the support of international partners, to find solutions to health challenges that have plagued the continent. To explore how the health professions communities of participating institutions have been impacted by AFREhealth and how the wider society consisting of key health professions education and research stakeholders and service consumers has benefitted from AFREhealth’s presence on the continent. The evaluation will identify lessons learned and how to apply them to improve AFREhealth as a continental organization. This qualitative study utilized focus group discussions and key informant interviews. Interviews were recorded and transcribed verbatim, and data analyzed thematically. A total of 57 registered members of AFREhealth participated in both key informant interviews (KIIs) and focused group discussions (FGDs). The respondents included health professionals, students in health profession’s education institutions, and others that have ever received support and services from AFREhealth
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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 | 0.053 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".