Children supervising children across low- and middle-income countries: the role of mothers’ education
Bibliographic record
Abstract
Around the world, many young children spend time supervising or being supervised by other children without adults. This can have both positive (e.g., strengthening sibling ties) and negative (e.g., hinder supervisor’s schooling) consequences for children, families, and communities. Population-based information from low- and middle-income countries (LMIC) is scarce on this phenomenon. Poisson random effect regression models using the most recent Multiple Indicator Cluster Surveys (MICS) and Demographic and Health Surveys (DHS) from 81 LMIC were built to estimate the prevalence of leaving children under five years-old under the supervision of another child younger than 10 years of age and the role of maternal education in this childcare arrangement. Prevalence of child-to-child supervision ranged from no supervision at all to 55.7% globally, with large variations across countries and regions. The highest prevalence was found in West and Central Africa. In 90% of the countries across all regions, higher maternal education was associated with lower prevalence rates of children supervised by another child. No clear pattern was found among the eight countries across four continents displaying the opposite trend. These findings call for context-based studies to identify determinants and consequences of this care arrangement and for continued support to mothers’ education to bolster the supervision and healthy development of child supervisors and supervisees.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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; both teacher heads agree on what is shown here.
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".