Unvaxxed and unafraid: Unvaccinated Americans perceive less disease risk than do vaccinated Americans
Bibliographic record
Abstract
Abstract Is disease risk perception accurately calibrated among the unvaccinated? People shift their attitudes to rationalize their choices, so those who choose to be unvaccinated may be motivated to feel less at risk. In three studies (total N = 1446), we asked Americans how worried they were about catching/spreading influenza and COVID‐19 and whether they were vaccinated against those diseases. Unvaccinated participants felt less at risk of catching/spreading the diseases they were unvaccinated against than vaccinated participants. For instance, unvaccinated participants felt ∼24% less at risk of catching/spreading COVID‐19 and had ∼28% stronger intention to engage in activities that carried a high risk of COVID‐19 transmission (Study 3). Overall, those who choose to be the most vulnerable to disease feel and act the least vulnerable.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".