Disseminating reliable health information through participatory radio programming on Indigenous language media: A study on selected community radio stations in rural Ghana
Bibliographic record
Abstract
This study is aimed to ascertain the role community media plays in the dissemination of reliable health information for rural community dwellers. By sampling three community radio stations in rural Ghana, the study presents a new perspective on how health dis/misinformation can be debunked through participatory programming and Indigenous language broadcasting on small community-owned mass media systems. Our study was influenced by the concept of informative fictions. We collected data using in-depth semi-structured interviews and a qualitative radio programme analysis of the health programmes of the participating community radio stations. Our study found that commercial media, herbal medicine practitioners and religious leaders play key roles in the spread of health dis/misinformation in rural Ghana. It was also found that, community radio presents an opportunity for local community health workers, such as medical doctors and district health promotion officers, to be involved in producing and broadcasting reliable health information to the members of their communities. The study concludes that whereas trust in religious leaders and herbal medicine practitioners promotes the spread of health dis/misinformation, programme producers and health workers who participate in health programme production in community radio stations can also capitalize on the trust of their community members to debunk health disinformation.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".