Sibling spillovers and the choice to get vaccinated: Evidence from a regression discontinuity design
Bibliographic record
Abstract
We investigate the effects of introducing population-wide free-of-charge Human Papillomavirus (HPV) vaccination programs on the targeted adolescent cohorts and their siblings. For identification, we rely on regression discontinuity designs and high-quality Danish administrative data to exploit that date of birth determines program eligibility. We find that the programs increased the HPV vaccine take-up of both the targeted children (53.2 percentage points for girls and 36.0 percentage points for boys) and their older same-sex siblings (4.5 percentage points for sisters and 3.5 percentage points for brothers). We show that while the direct effects of the programs reduced HPV vaccine take-up inequality, the spillover effects, in contrast, contributed to an increase in vaccine take-up inequality highlighting the potential importance of spillover effects in the determination of distributional consequences of public health programs. Finally, we find some evidence of cross-vaccine spillovers.
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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 | 0.025 | 0.068 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".