Short- and Long-Term Effects of Superhero Media on Young Children’s Risk-Taking Behaviors
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: Unintentional injuries, the leading cause of death for American children, are caused by a range of psychosocial factors, including risk behavior. One factor that may impact child risk-taking is modeling of superhuman risk-taking from superhero media, both immediately following superhero exposure and based on lifetime exposure and engagement. METHODS: Fifty-nine 5-year-olds were randomly assigned to view either a 13-min age-appropriate superhero television show or a comparable nonsuperhero show. After the viewing, children engaged in three risk-taking measures: (a) activity room, unsupervised play for 5 min with assortment of apparently dangerous items that might encourage child risk-taking; (b) picture sort, 10 illustrations of children in risk situations, with participant response concerning intended risk-taking in that situation; and (c) vignettes, 10 stories presenting situations with varying degrees of risk, with participant response on intended choice. Parents completed questionnaires concerning children's long-term superhero media exposure and individual superhero engagement (e.g., if child's most recent Halloween costume was of a superhero). Correlations and regressions evaluated effects of immediate superhero exposure, lifetime superhero exposure, and lifetime superhero engagement on children's risk-taking. RESULTS: Mixed results emerged. Lifetime superhero exposure was significantly related to children's risk-taking outcomes in two bivariate (vignettes and picture sort) and one multivariate (picture sort) model. Neither immediate superhero exposure nor lifetime superhero engagement was strongly related to risk-taking. CONCLUSIONS: Children's lifetime superhero exposure may influence children's risk-taking. Given American children's substantial media exposure, research should continue to unpack the role of superhero media on children's unintentional injury and other health risk behaviors.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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