Expanded child support grant eligibility and later-life mortality among mothers in rural South Africa
Bibliographic record
Abstract
The South African Child Support Grant (CSG) may be associated with mother's mortality via pathways linked to CSG spending, however, this relationship remains uncertain. To identify the association between CSG eligibility and mortality among mothers, we exploited exogenous variation in CSG-eligibility due to iterative age-eligibility expansions. Data were obtained from the Agincourt Health and Socio-Demographic Surveillance System. Mothers contributed person-time from age 50 till they died or were censored in March 2022. The cumulative duration of CSG-eligibility was calculated using children's birthdates and CSG expansion years and dichotomised at the median to give high (>18) and low (≤18) duration. We matched mothers with high vs low duration of CSG-eligibility based on their birth years and number of children. To estimate the association between cumulative duration of CSG eligibility by age 50 and subsequent all-cause mortality, we specified Cox proportional hazards models, adjusting for sociodemographic variables. Duration of CSG-eligibility was not associated with mortality among mothers in the full sample (adjusted HR: 1.05, 95% CI: 0.75, 1.44) nor within sociodemographic sub-groups. Future studies should explore the association of CSG eligibility with premature and cause-specific mortality in mothers and at different life course timings to promote their health and longevity.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".