Preventing Unintentional Injuries to Young Children in the Home: Understanding and Influencing Parents’ Safety Practices
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
Abstract Unintentional injuries are the leading cause of preventable deaths for children in most industrialized countries. In this article, I consider research on how parents prevent home injuries to children under 6 years and discuss an intervention aimed at improving parents’ home-safety practices. Parents of young children use three types of home-safety practices: teaching about safety, modifying the environment, and supervising. Relying predominantly on teaching increases young children's risk of injury, whereas modifying the environment and supervising protect children and predict fewer injuries. Drawing on evidence about factors that motivate parents’ safety practices, an intervention was developed to improve supervision: The Supervising for Home Safety program positively changed parents’ appraisals about injury and supervision practices. Developing evidence-based injury-prevention programs is an effective way to address this national public-health issue.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it