Who Complies and Who Defies? Personality and Public Health Compliance
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
During the first wave of the pandemic, governments introduced public health measures in an attempt to slow the spread of the virus enough to “flatten the curve”. These measures required behavioral changes among ordinary individuals for the collective good of many. We explore how personality might explain who complies with social distancing measures and who defies these directives. We also examine whether providing people with information about the expected second wave of the pandemic changes their intention to comply in the future. To do so, we draw upon a unique dataset with more than 1,700 respondents. We find honest rule-followers and careful and deliberate planners exhibit greater compliance whereas those who are entitled, callous, and antagonistic are less likely to engage in social distancing. Our experimental results show that even small differences in messaging can alter the effect of personality on compliance. For those who are more fearful and anxious, being confronted with more information about the severity of the second-wave resulted in higher levels of anticipated social distancing compliance. At the same time, we find that the same messages can have the unintended consequence of reducing social compliance among people higher in Machiavellianism.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.004 |
| 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