The Impact of Childcare on Poor Urban Women’s Economic Empowerment in Africa
Bibliographic record
Abstract
Despite evidence from other regions, researchers and policy-makers remain skeptical that women's disproportionate childcare responsibilities act as a significant barrier to women's economic empowerment in Africa. This randomized control trial study in an informal settlement in Nairobi, Kenya, demonstrates that limited access to affordable early childcare inhibits poor urban women's participation in paid work. Women who were offered vouchers for subsidized early childcare were, on average, 8.5 percentage points more likely to be employed than those who were not given vouchers. Most of these employment gains were realized by married mothers. Single mothers, in contrast, benefited by significantly reducing the time spent working without any loss to their earnings by shifting to jobs with more regular hours. The effects on other measures of women's economic empowerment were mixed. With the exception of children's health care, access to subsidized daycare did not increase women's participation in other important household decisions. In addition, contrary to concerns that reducing the costs of childcare may elevate women's desire for more children, we find no effect on women's fertility intentions. These findings demonstrate that the impact of subsidized childcare differs by marital status and across outcomes. Nonetheless, in poor urban Africa, as elsewhere, failure to address women's childcare needs undermines efforts to promote women's economic empowerment.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".