Warmth and competence perceptions of key protagonists are associated with containment measures during the COVID-19 pandemic: Evidence from 35 countries
Bibliographic record
Abstract
= 12,553) from 6 continents during the COVID-19 pandemic (between 2021 and 2022) obtained via cross-sectional surveys that the social perception of key protagonists on two basic dimensions-warmth and competence-plays a crucial role in shaping pandemic-related behaviors. Firstly, when asked in an open question format, heads of state, physicians, and protest movements were universally identified as key protagonists across countries. Secondly, multiple-group confirmatory factor analyses revealed that warmth and competence perceptions of these and other protagonists differed significantly within and between countries. Thirdly, internal meta-analyses showed that warmth and competence perceptions of heads of state, physicians, and protest movements were associated with support and opposition intentions, containment and prevention behaviors, as well as vaccination uptake. Our results have important implications for designing effective interventions to motivate desirable health outcomes and coping with future health crises and other global challenges.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".