The effect of babies on mother’s labor supply by education and race
Bibliographic record
Abstract
This book looks at how mother's education and race are important determinants of the size, pattern, and even the sign of the effect of young children on their mother's labor supply. Children less than three years old are one of the most important causes of interruptions and changes in women's labor supply. It extends over the USA over the last quarter of the 20th century, a period of time when the labor force participation of mothers with babies shows a higher growth rate than that of women with older children or without children. This study estimates different static labor supply models using the biggest annual survey conducted by the Bureau of the Census and analyzes the decision to work at the extensive and intensive margins as well as the distribution of hours of work. Although highly educated women have the highest labor force participation rate, and the highest number of worked hours when they have babies, they are the most affected by young children showing the greatest degree of flexibility to adjust the number of hours of work. The differences between black and white women are notorious both in the degree and sign of the response to the presence of babies and in the trend.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.018 | 0.002 |
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".