Balancing paid work and child care in a slum of Nairobi, Kenya: the case for centre-based child care
Bibliographic record
Abstract
As a growing number of women across sub-Saharan Africa engage in paid work, they face the challenge of finding suitable child care arrangements. Drawing on survey data from over 1,200 mothers and in-depth interviews with 31 of these women, we find that mothers living in a slum of Nairobi, Kenya, employ three main strategies to balance their work and child care responsibilities: (1) combine work and child care, (2) rely on kin and neighbours, or (3) use centre-based care. Mothers reported numerous disadvantages to either bringing their children to work or depending on others for child care assistance. In contrast, mothers highlighted several perceived benefits of centre-based child care for themselves and their children, while noting that costs were often prohibitive. These findings suggest that providing affordable centre-based child care could be a key strategy to improving the lives and welfare of women and children living in African slums.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.023 | 0.014 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".