Does Maternal Employment Affect Child Nutrition Status? New Evidence from Egypt
Bibliographic record
Abstract
Despite that maternal employment can increase family income; several studies suggest that it has adverse health consequences for children. The literature on the effects of maternal employment on children in the Middle East and North Africa (MENA) is sparse. In this study, we assess the impact of maternal employment on children’s health in Egypt, the most populous country in the MENA region. We use a nationally representative sample of 12, 888 children under the age of five from 2014 Demographic and Health Survey for Egypt, to estimate the causal impact of mothers’ employment on their children’s nutritional status, as measured by the Height-for-Age Score (HAZ). We adopt various estimation methods and control for observed and unobserved household characteristics to identify the causal effect of maternal employment. These different techniques include Propensity Score Matching (PSM), and an Instrumental Variable Two Stage Least Squares approach. We find that maternal employment has a robust negative impact on child nutritional status in Egypt. However, the effect of maternal employment is understated when the Ordinary Least Squares and PSM are applied. More family-friendly policies for working moms are strongly needed in Egypt.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".