A Brief Look at Vicarious Trauma in Meteorologists and Emergency Management Professionals: Preliminary Evidence, Associated Coping Behaviors, Emotion Regulation Strategies, Pathological Altruism, and Healthy Selfishness
Bibliographic record
Abstract
This paper briefly and preliminarily examines, based on data collected in mid-2020, vicarious traumatization in 154 meteorologists and emergency managers. This topic is of great importance, considering that weather-focused individuals providing disaster and even more routine weather forecast support may take on variations of the stress they witness in or that they imagine exists for their constituents, leading to myriad negative mental health outcomes. The study explores this phenomenon, focusing on the collaborative nature of the weather enterprise and the proximity of emergency management personnel to meteorological contexts. Despite moderate levels of vicarious traumatization in the weather enterprise, at least as evidenced within this sample, findings suggest relative stability in individual differences across meteorological employment sectors, with no substantial trends. Differences emerged in pathological altruism and overall mental health coping scores, with emergency management professionals scoring higher in the former and television-broadcast meteorologists in the latter. Generally, emergency management professionals exhibit higher pathological altruism compared to government and broadcast meteorologists, suggesting that meteorologists place relatively healthy boundaries between themselves and their work and thus buffering negative mental health outcomes. Overall and speaking preliminarily, meteorologists seem fairly psychologically resilient in the face of vicarious traumatization.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".