Physical Disability, Rights and Stigma in Ghana: A Review of Literature
Bibliographic record
Abstract
Purpose: This is a survey of peer-reviewed articles focussed on the causes and consequences of stigma towards persons with physical disability in Ghana. Method: After a systematic search of the online databases EBSCOhost, ProQuest, PubMEd and Web of Science for peer-reviewed articles on disability in Ghana, 26 articles were chosen for critical review. The three main selection criteria were: the articles had to be peer-reviewed, they had to be based on interviews with Ghanaians in the field, and they had to discuss stigma and human rights. For analysis, the content of the articles was grouped under two sections: major themes (human rights, causes of stigma, consequences of stigma) and policy recommendations (economics, medical services/healthcare, affirmative action, attitudes and awareness-raising, inclusion of cultural beliefs). Results: This review found that most of the studies attribute stigma to negative attitudes towards Ghanaians with disability, and many highlight beliefs among Ghanaians that disability is caused by spiritual and supernatural forces. The consequences, according to most authors, are social, economic and political exclusion. Policy recommendations include improving government policy, increasing funding for disability programmes, changing public attitudes, and paying attention to Ghanaian culture and tradition in designing disability interventions. While these are valid points, the authors of this paper are of the opinion that the literature also suffers from lack of a deep understanding of the historical and socio-cultural roots of supernatural beliefs in Ghana. Conclusion: The 26 studies discussed in this review show that since 2006 very good work has been produced on disability in Ghana, especially by Ghanaian disability scholars. It is hypothesised, however, that a full understanding of disability and stigma in Ghana must be based on deeper research into the roots of the beliefs that drive stigma. Future work therefore should focus on deepening the analysis of cultural beliefs towards disability in Ghana, in order to understand fully the roots of culturally-based disability stigma. More research into the economic causes and consequences of disability is also recommended, without which a full analysis of cultural stigma will not be possible.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".