The COVID States Project #49: Vaccinating America's youth
Bibliographic record
Abstract
With Pfizer’s COVID-19 vaccine soon to be available to 12-15-year-olds, how prepared are Americans to vaccinate their children? And do they support requiring that children be vaccinated before returning to in-person school? In this report, we examine three aspects of childhood vaccinations: parents’ resistance to vaccinating their children, support among all adults for making vaccinations a requirement in schools, and attitudes towards vaccination among youth. Below are our key findings:● Since February, the gap in attitudes between fathers and mothers has widened. While fathers became marginally less resistant, falling from 14% to 11% since February, over a quarter of mothers still say they are “extremely unlikely” to vaccinate their children.● Educational, income, and partisan divides in childhood vaccination attitudes have become more pronounced. Parents in households making less than $25,000 per year, parents without a college degree, and Republican parents have become more resistant to vaccinating their children. Resistance has decreased for college-educated, high income, and Democratic parents.● Parents of teenagers are less resistant to having their children vaccinated than parents of small children, and—in the case of mothers—slightly more supportive of school vaccination requirements.● Support for school vaccination requirements has grown slightly from 54% to 58%. This increase holds for most gender, race, and income categories. However, among Republicans, support remains virtually unchanged.● Mothers are less likely to support school vaccination requirements than other women, while fathers are more likely to support school vaccination requirements than other men.● Among youth who are old enough to get vaccinated without parental consent (18-21-year-olds), one five are vaccine resistant.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".