The Long-Run Effects of California’s Paid Family Leave Act on Women’s Careers and Childbearing: New Evidence from a Regression Discontinuity Design and U.S. Tax Data
Bibliographic record
Abstract
This paper uses IRS tax data to evaluate the short-and long-term effects of California's 2004 Paid Family Leave Act (PFLA) on women's careers. Our research design exploits the increased availability of paid leave for women giving birth in the third quarter of 2004 (just after PFLA was implemented). These mothers were 18 percentage points more likely to use paid leave but otherwise identical to multiple comparison groups in pre-birth demographic, marital, and work characteristics. We find little evidence that PFLA increased women's employment, wage earnings, or attachment to employers. For new mothers, taking up PFLA reduced employment by 7 percent and lowered annual wages by 8 percent six to ten years after giving birth. Overall, PFLA tended to reduce the number of children born and, by decreasing mothers' time at work, increase time spent with children.
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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 | 0.011 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".