“Please keep an eye on your younger sister”: sibling supervision and young children's risk of unintentional injury
Bibliographic record
Abstract
OBJECTIVES: Parental supervision reduces young children's risk of unintentional injuries, but supervision by older siblings has been shown to increase risk. The current study explored how this differential risk of injury may arise. METHODS: The supervision behaviours of mothers were compared to those of their older children when each was the designated supervisor of a young child in their family in a setting having 'contrived hazards'. RESULTS: Mothers engaged in more proactive safety behaviours by removing hazards, whereas older siblings more often modelled injury-risk behaviours by interacting with hazards, and supervisees were likely to interact with hazards the older sibling touched. Supervisees displayed more injury-risk behaviours when supervised by a sibling, yet sibling supervisors were less attentive to supervisee risk behaviours than mothers. Supervisees also were more non-compliant with older siblings than mothers when requested to stop risk taking. CONCLUSIONS: Both supervisor and supervisee behaviour patterns contribute to increase the risk of injury when older siblings supervise younger ones.
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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 | 0.004 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".