Consequences of HIV Infection on Household Assets and Human Capital Investment in Uganda: Micro Evidence
Bibliographic record
Abstract
This paper studies the effect of the HIV and AIDS epidemic on economic decision making using the Uganda National Household Survey (2010). The findings indicate that household’s HIV and AIDS status, education and social-economic factors are important in explaining low household’s asset accumulation and school enrolments of children in Uganda especially at primary school level. Household savings and assets accumulation findings show that household’s HIV and AIDS status and their education levels, marital status and the employment status are consistently associated with lower savings. Major implications of these results is that raising women’s education improves their economic opportunities and the behavioral responses in sexual interaction will lead to decline in HIV infection by reducing the willingness to engage in unprotected sex. In fact, we find that educational performance declines in those HIV infected households in which the father is living with HIV. The paper recognizes the policy challenges surrounding the HIV and AIDS -education linkage and considers some of the strategies that have been implemented to improve the schooling outcomes of children from households of people living with HIV (PLHIV). We find a weak positive effect of HIV infection on savings and a significant positive effect on school enrolment and educational expenses for children. High-perceived infection risk has a positive albeit imprecise influence on school enrollment and educational expenses, but no effect on savings.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".