Exploring the Interplay Between Threat Appraisal, Efficacy Appraisal, and Behavior Change During a “Once-in-a-Lifetime” Storm
Bibliographic record
Abstract
In 2022, Hurricane Fiona made landfall in Atlantic Canada, causing widespread destruction across the region. The storm provided the opportunity to test the Extended Parallel Process Model (EPPM), which predicts that warning messages influence threat appraisal and efficacy appraisal, and in turn influence whether individuals engage in fear control processes or danger-control processes. To do so, a questionnaire was disseminated to residents of Atlantic Canada (n=582) approximately two weeks after the storm. The results find that respondents generally fell in one of two protective action classes: low protective action and high protective action. Efficacy appraisal had no effect on whether or which actions respondents took during the storm. In contrast, anxiety and information seeking were both found to be significant. The results seemingly contradict previous research on fear appeals guided by the EPPM. In our conclusion, we speculate on why this may be and recommend several opportunities for future research.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".