The Longitudinal Dynamics of Household Composition and Wealth in Rural Malawi
Bibliographic record
Abstract
Household living arrangements play a crucial role in survival efforts throughout sub-Saharan Africa. Household living arrangements foster the development of informal insurance that can mitigate economic or filial shocks, and potentially improve the overall well-being of kin. However, scholarship in sub-Saharan African settings has not been able to, or has not attempted, to track how households have changed and the coinciding changes in livelihood outcomes. We ask whether changes in overall household size and the addition of dependents and working-age individuals are associated with changes in household wealth, a signal of well-being. We use the Malawi Longitudinal Study of Families and Health (MLSFH) to exploit detailed data on changing Malawian household composition via a household roster matching technique and fixed effects regressions. The addition of members to a household and the presence of more boys and working-age men—to a certain point—are associated with having more durable goods and greater chances of acquiring a metal roof—key indicators of wealth in rural Malawi. The addition of girls and women of any age are seemingly not linked to changes in household wealth.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".