Paid family leave and reduced acute respiratory infections in young infants: does everyone benefit equally?
Bibliographic record
Abstract
To examine whether the effect of a paid family leave program on acute care encounters for respiratory tract infections among young infants differed by subgroups. We examined 52 943 hospitalizations and emergency department visits between October 2015 and February 2020 among infants aged ≤8 weeks in New York, which introduced paid family leave in January 2018, and four New England control states (Massachusetts, New Hampshire, Vermont, and Maine). We conducted a controlled time series analysis that compared observed counts in New York during the putative respiratory virus season (October to March) in each population subgroup to those predicted in the absence of the policy. Absolute reductions in respiratory tract infection-related acute care encounters among young infants were greater for Hispanic as compared to non-Hispanic White infants (5.60 fewer cases per 1000 infants [95% CI, -8.74 to -2.51]) and for encounters paid for by Medicaid as compared to private payer (4.22 fewer cases per 1000 [95% CI, -6.45 to -2.18]). Findings by Child Opportunity Index 2.0 quintiles showed no clear pattern. Our findings suggest the program may have larger benefits for infants from less advantaged groups.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".