Cash Transfer Programmes For Reducing Poverty And Vulnerabilities: Effects On Children’s Health In Sub-Saharan Africa And Latin America
Bibliographic record
Abstract
This paper summarizes the arguments and counterarguments within the scientific discussion on cash transfers and child health. The main purpose of the research is to assess the effects of cash transfers on children’s health and development outcomes in sub-Saharan Africa and Latin America. Systematization of the literary sources indicates that studies have justified cash transfer as social-income support that addresses a vital social determinant of health (income) for children in low-and-middle-income countries. The methodological basis of this study is a systematic review that searched a wide range of electronic databases such as PubMed, ResearchGate and ScienceDirect. Studies included in this review included randomized controlled trials (RCTs), cluster-RCTs, quasi-experimental and mixed methods studies of cash transfer interventions in children 0-18 years. Inclusion criteria were met by eight studies, four from Africa and four from Latin America. The systematic review presents the results of data synthesis of the included studies that mainly reported the effects of cash transfer programmes on child anthropometry outcomes, cognitive development, morbidity, and healthcare utilization. The review found cash transfer programmes to improve these variables among children in households receiving cash transfers. This systematic review has added to the debate on cash transfers and children’s health outcomes. In general, the systematic review indicates that cash transfer programmes intended for children are effective at improving anthropometric, health, and cognitive outcomes, as well as access to healthcare. However, there is a need for more research to clarify the multiple pathways by which cash transfers can improve children’s health and nutritional outcomes. It is also necessary to clarify what factors explain the variety of effects of cash transfer programs on child health and nutritional status. Finally, cash transfer interventions are not permanent mechanisms for promoting access to healthcare. Policymakers in developing countries should borrow ideas on how to finance healthcare services for improving the socio-economic wellbeing of citizens.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".