Gender and Poverty in South Africa in the Era of HIV/AIDS: A Quantitative Study
Bibliographic record
Abstract
BACKGROUND: Recent research identifies gender inequality as a driver of the HIV/AIDS epidemic. The feminization of poverty is also increasingly apparent, as is the disproportionate vulnerability of members of female-headed households. We sought to examine the relationships among sex, gender, age, HIV status, and socioeconomic characteristics, focusing on heads and nonheads of households. METHODS: We interviewed 6,338 men and 10,057 women. RESULTS: Significantly more males (51.4%) than females (34.8%) indicated that they were heads of households (p < 0.001). Female heads of households were significantly more likely to be infected with HIV than their male counterparts (17.9% vs. 13.1%). Among 15-24-year-old males, those who are often without cash are more likely to be infected with HIV than those who are never without cash (OR = 3.33, 95% CI 1.17-9.49). Similar results were observed among females, who sometimes had no cash (OR = 1.86, 95% CI 1.22-2.82), and among adults aged >or=25 years. Results confirmed that age and gender are related to HIV infection in South Africa and that poverty is a social determinant for HIV infection across all age groups. However, sex is a determinant only among the younger age groups. Young female heads of household are more likely to be poor and are more likely to be HIV positive. CONCLUSIONS: The results indicate that the HIV/AIDS epidemic in South Africa is characterized by gender inequalities. Young women are more likely to be HIV infected, especially heads of households. Young women are also more likely to live in poverty, although this study cannot establish the directionality of a causative relationship between poverty and risk of HIV. Greater attention must be paid to young women, especially those who head households, in terms of treatment, prevention, and poverty alleviation.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.002 |
| 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".