Socio‐economic differences in <scp>HIV</scp>/<scp>AIDS</scp> mortality in South Africa
Bibliographic record
Abstract
OBJECTIVES: To quantify socio-economic differences in the risk of HIV/AIDS mortality in South Africa for different measures of socio-economic status. METHODS: Systematic literature search in Web of Knowledge and PubMed. Measures of relative risk (RR) were pooled separately for education, income, assets score and employment status as measures of socio-economic status, using inverse-variance weighted DerSimonian-Laird random effects meta-analyses. RESULTS: Ten studies were eligible for inclusion comprising over 175 000 participants and 6700 deaths. For income (RR 1.55, 95% confidence interval (CI) 1.15-2.09), assets score (RR 1.63, 95% CI 1.12-2.36) and employment status (RR 1.52, 95% CI 1.21-1.92), persons of low socio-economic status had an over 50% higher risk of dying from HIV/AIDS. The RR of 1.10 for education was not significant (95% CI 0.74-1.65). CONCLUSIONS: Future research should identify effective strategies to reduce HIV/AIDS mortality and alleviate the consequences of HIV/AIDS deaths, particularly for poorer households.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".