How did South Africans with disabilities experience COVID-19? Results of an online survey
Bibliographic record
Abstract
Background: People with disabilities are a large, disadvantaged minority, comprising approximately 12% of the population. The South African government has ratified international and regional disability treaties but deals with disability rights within general anti-discrimination legislation. There are no specific frameworks to monitor justice for people with disabilities. The study aims to inform further development of disability inclusive mechanisms relating to crises including pandemics. Objectives: This study explored the perceptions of South Africans with disabilities, to understand their experiences during coronavirus disease 2019 (COVID-19), focussing on socioeconomic, well-being and human rights aspects. Method: An online survey tool generated quantitative and qualitative data. Widespread publicity and broad recruitment were achieved through project partners networks. Participants responded via mobile phone and/or online platforms. Results: Nearly 2000 people responded, representing different genders, impairments, races, socio-economic status, education and ages. Findings include: (1) negative economic and emotional impacts, (2) a lack of inclusive and accessible information, (3) reduced access to services, (4) uncertainty about government and non-government agencies' support and (5)exacerbation of pre-existing disadvantages. These findings echo international predictions of COVID-19 disproportionally impacting people with disabilities. Conclusion: The evidence reveals that people with disabilities in South Africa experienced many negative impacts of the pandemic. Strategies to control the virus largely ignored attending to human rights and socioeconomic well-being of this marginalised group. Contribution: The evidence will inform the development of the national monitoring framework, recognised by the South African Government and emphasised by the United Nations as necessary to ensure the realisation of the rights of people with disabilities during future crises including pandemics.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".