File Drawer Report: A Preliminary Test of Video-Mediated Severe Weather Exposure and Note on the Potential Role of Mindfulness in Decreasing Storm-Associated Negative Affect
Bibliographic record
Abstract
Research at the intersection of meteorology and societal impacts is increasingly important. Still, it is relatively rare for this work to take on a psychological frame. Here, we blend media and positive psychology topics with the judgement and decision-making domain for a multifaceted investigation into psychological and behavioral responses to severe and dangerous weather conditions. Using a simple pre/post, quasi-experimental design, we tested the following predictions: 1) Exposure to dangerous weather conditions, via video-based multimedia, would increase participants’ negative affect and weather-related fear; 2) video-mediated storm exposure would increase participants’ intent to engage in future protective actions; and 3) a brief mindfulness exercise would significantly lower the weather-induced negative affectivity. Resource unavailability meant we were unable to conduct a full experiment including a control group. However, all three hypotheses were confirmed and we believe our findings warrant further replication. Results indicated a small but significant (apparent) effect of mindfulness in reducing negative affect when controlling for lived storm experience and positive affect brought on by storm-associated awe and excitement (η_G^2 = 0.02), and small to moderate effects of multimedia exposure on increases in protective action intentions (d = –0.71), and weather fear (d = –0.24). Results are discussed in light of meteorological communication principles, the existing literatures on mindfulness and protective action responses to severe weather, and the potential for mindfulness interventions in psychological responses to severe and dangerous weather.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".