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Record W2059149795 · doi:10.1136/ip.2010.026377

“Please keep an eye on your younger sister”: sibling supervision and young children's risk of unintentional injury

2010· article· en· W2059149795 on OpenAlexaff
Barbara A. Morrongiello, Stacey L. Schell, Sarah Schmidt

Bibliographic record

VenueInjury Prevention · 2010
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsUniversity of Guelph
FundersNational Center for Injury Prevention and Control
KeywordsSisterSiblingInjury preventionPoison controlOccupational safety and healthSuicide preventionHuman factors and ergonomicsForensic engineeringEngineeringMedical emergencyMedicinePsychologyDevelopmental psychologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.356
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.018
GPT teacher head0.328
Teacher spread0.310 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations22
Published2010
Admission routes1
Has abstractyes

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