Reducing albinism related stigma in Tanzania: an exploration of the impact of radio drama and radio interview
Bibliographic record
Abstract
Reducing stigma is key to improving the wellbeing of people with albinism in Tanzania. This study aimed to obtain more insight into the effects of two radio interventions with regard to albinism-related stigma: a radio drama and a radio interview. Assessment of the radio interventions was based on two attitude measurement instruments (The Albinism Explanatory Model Interview Catalogue Community Stigma Scale and the Albinism Social Distance Scale), an entertainment scale, and two informal (group) interviews. In total, 111 community members participated in the assessment prior to the radio drama, and 65 after. In the case of the radio interview, 123 community members participated in the assessment prior to the radio show, and 77 after. Following the radio drama, a significant reduction was found in terms of community stigma, and a reduction in social distance was found after both interventions. The entertainment score for both interventions was high, but significantly higher for the radio drama. The respondents indicated that they had gained more understanding of albinism as a result of the interventions, and were positive about this type of education. The current study shows that a radio show in which the listener interacts with someone with albinism can contribute to a reduction in stigma, and demonstrates that different types of radio intervention can have different outcomes. Points of interestReducing discrimination is key to improving the wellbeing of people with albinism in Tanzania.This research investigated the use of radio shows to change attitudes towards people with albinism within the community; two types of radio show were tested: a radio drama and a radio interview.Through the shows the respondents got into contact with someone with albinism.The shows were valued by the community members as an attractive means of education.The shows proved to be effective in terms of improving peoples’ knowledge about, and attitude towards people with albinism.People enjoyed the radio drama more than the radio interview. The radio drama was also more effective than the radio interview in improving peoples’ attitudes towards people with albinism.This research offers recommendations for organisations that are working to raise awareness with regard to albinism.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".