Intentions to be Vaccinated Against COVID-19: The Role of Prosociality and Conspiracy Beliefs across 20 Countries
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
Understanding the determinants of COVID-19 vaccine uptake is important to inform policy decisions and plan vaccination campaigns. The aims of this research were to: (1) explore the individual- and country-level determinants of intentions to be vaccinated against SARS-CoV-2, and (2) examine worldwide variation in vaccination intentions. This cross-sectional online survey was conducted during the first wave of the pandemic, involving 6697 respondents across 20 countries. Results showed that 72.9% of participants reported positive intentions to be vaccinated against COVID-19, whereas 16.8% were undecided, and 10.3% reported they would not be vaccinated. At the individual level, prosociality was a significant positive predictor of vaccination intentions, whereas generic beliefs in conspiracy theories and religiosity were negative predictors. Country-level determinants, including cultural dimensions of individualism/collectivism and power distance, were not significant predictors of vaccination intentions. Altogether, this study identifies individual-level predictors that are common across multiple countries, provides further evidence on the importance of combating conspiracy theories, involving religious institutions in vaccination campaigns, and stimulating prosocial motives to 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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 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 it