Media-Induced War Trauma Amid Conflicts in Ukraine
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
War could be traumatic. War trauma could often lead to severe and sustained health consequences on people's physical and psychological health. War trauma is often prevalent in people who either participated in the war or lived near conflict zones, such as military professionals, refugees, and health workers. Advances in information and communication technologies, such as the speed, scale, and scope at which people worldwide could be exposed to the near-time happenings of the war, mean that an unprecedented number of people could face media-induced war trauma. Different from war experienced in person, which could be limited in scope and intensity, media-induced war trauma can be substantially more extensive and comprehensive-news reports on the war often cover all aspects and angles possible, possibly paired with disturbing, if not demoralizing, images, repeatedly 24/7. Although media-induced war trauma could have a profound influence on people's mental health, particularly factoring in the compounding challenges caused by the pandemic, there is a dearth of research in the literature. To shed light on this issue, in this article, we aim to examine the implications of media-induced war trauma on people's health and well-being. Furthermore, we discuss the duties and responsibilities of the media industry amid and beyond the current conflicts in Ukraine.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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