Access to health care in South Africa--the influence of race and class.
Bibliographic record
Abstract
OBJECTIVES: The first democratic government elected in South Africa in 1994 inherited huge inequities in health status and health provision across all sections of the population. This study set out to assess the impact of the new government's commitment to address these inequities and implement policies to improve population health in general and address inequalities in health care in particular. DESIGN: A 1998 household survey assessed many aspects of health delivery, including their own perceived and actual access to health care among different segments of South African society. RESULTS: Race was the main predictor of perceived changes in access to health care, with black, coloured-and Indian respondents significantly more likely to feel that access had improved since 1994, compared with white respondents. Socio-economic status (SES) was the main predictor of actual access to health care, with low and middle SES classes significantly less likely to access care when ill. CONCLUSIONS: One-third of respondents perceived health care access to have improved between 1994 and 1998, and this response was partially determined along racial lines. About one-quarter reported an inability to access health care when they required it, and this response was partially determined along socio-economic lines. This set of contrasting responses suggests that at a political level perceptions are largely influenced by race, but at the operational level actual access is influenced by SES.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".