Don’t Touch the Gadget Because It’s Hot! Mothers’ and Children’s Behavior in the Presence of a Contrived Hazard at Home: Implications for Supervising Children
Bibliographic record
Abstract
OBJECTIVE: This study compared boys' with girls' hazard-directed behaviors at home when the mother was present and absent from the room. METHODS: Videos were coded for how children reacted to a contrived burn hazard ('Gadget'), maternal verbalizations to children about the hazard, and children's compliance with directives to avoid the hazard. Children's behavioral attributes (risk-taking tendency, inhibitory control) and maternal permissive parenting style were also measured. RESULTS: Boys engaged in more hazard-directed behaviors when the mother was present than absent, whereas girls' risk behaviors did not vary with caregiver presence and was comparable with how boys behaved when the parent was absent. Mothers emphasized reactive communications, and boys received significantly more of these than girls. Permissiveness was associated with fewer statements explaining about safety. Children high in inhibitory control showed fewer hazard-directed behaviors and greater compliance with parent communications, whereas those high in risk-taking propensity showed more hazard-directed behaviors and less compliance. CONCLUSIONS: The hazard-directed behaviors of boys and girls vary with caregiver context, with boys reacting to parent presence with increased risk taking. Depending on child attributes, different supervision patterns are needed to keep young children safe in the presence of home hazards.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".