Fear about adverse effect on fertility is a major cause of COVID‐19 vaccine hesitancy in the United States
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Although COVID-19 vaccine access has increased nationwide, vaccination rates have been slow-moving, with many studies showing significant vaccine hesitancy in the U.S. We conducted an online survey using Amazon Mechanical Turk (MTurk) to identify reasons for vaccine hesitancy among unvaccinated adults between June 30 and July 1, 2021. We found that 58% of unvaccinated respondents were worried about unknown long-term adverse effects. Of these, 41% believed that the COVID-19 vaccines can negatively impact reproductive health and or fertility, and 38% were unsure of the effects on fertility. Our study demonstrates that fear regarding COVID-19 vaccine adverse effects and belief that they can negatively impact fertility is a major cause of vaccine hesitancy in the United States. We identified that urban residents, married individuals, those born outside the U.S., those with health insurance, and people with higher education and income greater than $100,000 felt that the vaccine would affect fertility more than their counterparts did. Finally, we found that 48% of unvaccinated respondents cited 'more information and research conducted on the COVID-19 vaccines' as the action that would most encourage vaccine uptake.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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 it