Intellectual humility predicts COVID‐19 preventive practices through greater adoption of data‐driven information and feelings of responsibility
Bibliographic record
Abstract
Abstract Preventive health practices have been crucial to mitigating viral spread during the COVID‐19 pandemic. In two studies, we examined whether intellectual humility—openness to one's existing knowledge being inaccurate—related to greater engagement in preventive health practices (social distancing, handwashing, mask‐wearing). In Study 1, we found that intellectually humble people were more likely to engage in COVID‐19 preventive practices. Additionally, this link was driven by intellectually humble people's tendency to adopt information from data‐driven sources (e.g., medical experts) and greater feelings of responsibility over the outcomes of COVID‐19. In Study 2, we found support for these relationships over time (2 weeks). Additionally, Study 2 showed that the link between intellectual humility and preventive practices was driven by a greater tendency to adopt data‐driven information when encountering it, rather than actively seeking out such information. These findings reveal the promising role of intellectual humility in making well‐informed decisions during public health crises.
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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 | 0.002 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".