Do cash transfer programmes yield better health in the first year of life? A systematic review linking low-income/middle-income and high-income contexts
Bibliographic record
Abstract
INTRODUCTION: Decades of research unequivocally demonstrates that no matter the society, socioeconomic resources are perhaps the most fundamental determinants of health throughout the life course, including during its very earliest stages. As a result, societies have implemented 'cash transfer' programmes, whichprovide income supplementation to reduce socioeconomic disadvantage among the poorest families with young children. Despite this being a common approach of societies around the world, research on effects of these programmes in low-income/middle-income countries, and those in high-income countries has been conducted as if they are entirely distinct phenomena. In this paper, we systematically review the international literature on the association between cash transfer programmes and health outcomes during the first year of life. METHODS: We conducted a systematic review based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol. Using a variety of relevant keywords, we searched MEDLINE, EMBASE, CINAHL, Cochrane Reviews, EconLit and Social Sciences Citations Index. RESULTS: Our review yielded 14 relevant studies. These studies suggested cash transfer programmes that were not attached to conditions tended to yield positive effects on outcomes such as birth weight and infant mortality. Programmes that were conditional on use of health services also carried positive effects, while those that carried labour-force participation conditionalities tended to yield no positive effects. DISCUSSION: Given several dynamics involved in determining whether children are healthy or not, which are common worldwide, viewing the literature from a global perspective produces novel insights regarding the tendency of policies and programmes to reduce or, to exacerbate, the effects of socioeconomic disadvantage on child health.
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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 | 0.009 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".