The Returns to Nursing: Evidence from a Parental-Leave Program
Bibliographic record
Abstract
Abstract In this article, we quantify the effects of nurses on health care delivery and patient health in the context of an unintended and policy-induced nurse shortage. Our empirical strategy takes advantage of a parental-leave program in Denmark, which offered any parent the opportunity to take up to one year’s absence per child aged 0–8. Combining the policy variation with administrative employer–employee match data, we document substantial program take-up among nurses, who could not be replaced on net despite public education and immigration expansion efforts to mitigate the employment effects. We find that the parental leave program reduced hospital and nursing home nurse employment by 15% and 10%, respectively. Using detailed patient health records, we find detrimental effects on hospital-care delivery as indicated by a large increase in 30-day readmission rates among acute myocardial infarction patients. We find no evidence for an increase in hospital mortality. In nursing homes, we estimate a large increase in mortality.
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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 | 0.008 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".