Interest groups, issue definition and the politics of traditional medicine in Ghana
Bibliographic record
Abstract
In some African societies, the highly accessible means of healthcare that has stood the test of time is traditional medicine. Though several actors have different views pertaining to its practice, traditional medicine continues to survive even in the age where biomedicine has become very reputable among African communities. Statistics have indicated that, 80% of Africans make use of traditional medicine before consulting any health practitioner in biomedicine. In the Ghanaian setting, traditional medicine users range from 75% to 90%. Using colonial Asante as a case study, which includes Ahafo, this article draws insight from a wide range of archival sources to highlight the various transformations underlying traditional medical practices in Asante and its environs. It argues this in the context of definitions and meanings attached to traditional medicine by actors such as the Ghana Psychic and Traditional Healers Association (GPTHA), the British Colonial Government in Asante, immediate post-colonial governments and Native Authorities who are at the centre of cultural norms in which traditional medicine features greatly. The findings suggest that the perspective of emerging healers who have modernised their practices, continue to have significant implications on healthcare in Ghana. It further postulates that their engagement has increased the functional scope of traditional medicine in Ghana.
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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.008 | 0.017 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 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".