The Impact of Child and Maternal Health Indicators on Female Labor Force Participation after Childbirth: Evidence for Germany
Bibliographic record
Abstract
This paper analyzes the influence of child health and maternal physical and mental health on female labor force participation after childbirth in Germany. Our analysis is based on data from the German Socio-Economic Panel (SOEP) study, which enables us to measure child health based on the occurrence of severe health problems including mental and physical disabilities, hospitalizations, and preterm births. Since child health is measured in SOEP at a very young age, we can rule out the reverse effects of maternal employment on child health that appeared in US studies. We investigate the influence of these indicators on various aspects of female labor force participation after childbirth within a two-year time period, including continuous labor force participation in the year of childbirth and the transition to employment in the year following childbirth. Since the majority of women in Germany do not go back to work within the first two years after childbirth, we also investigate their intention to return to work and their preferred number of working hours. We find that severe child health problems have a significant negative effect on maternal labor force participation and a significant positive effect on mothers’ preferred number of working hours, while hospitalizations and preterm births have no significant effect. For maternal health, we find a significant negative effect of poor maternal mental and physical health on female labor force participation within a year of childbirth. To our knowledge, this is the first empirical study of this kind using data from outside the US.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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; a candidate call from one teacher head, 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".