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Record W2475285640 · doi:10.3390/ijerph13070669

Children’s Understanding of No Diving Warning Signs: Implications for Preventing Childhood Injury

2016· article· en· W2475285640 on OpenAlexafffund
Barbara A. Morrongiello, Amanda Cox, Rachel Scott, Sarah E Sutey

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2016
Typearticle
Languageen
FieldMedicine
TopicInjury Epidemiology and Prevention
Canadian institutionsUniversity of Guelph
FundersCanadian Institutes of Health Research
KeywordsWarning signsWarning systemPsychologyInjury preventionHead and neckHuman factors and ergonomicsMedical emergencySuicide preventionOccupational safety and healthPoison controlMedicineDevelopmental psychologySurgeryEngineeringPathology

Abstract

fetched live from OpenAlex

The current study examined children's understanding of No Diving warning signs. Normally-developing 7 to 10 year olds were asked questions to assess their understanding of text, images, and main messages on No Diving warning signs. These structured interviews were audio recorded and responses were later coded. Results revealed that children understood the behavior advised against (diving), why it is prohibited (can hit head on the bottom), and what can happen (serious injury including hospitalization). They understood that breaking your neck results in limitations in mobility and can occur from diving, but they did not anticipate that such an injury is likely to occur. There were no gender and few age differences, but diving experience was associated with children significantly downplaying their risk of injury. The findings suggest that having No Diving warning signs explicitly mention a broken neck, may serve to remind children of this potential consequence at the time of decision making. Active adult supervision is particularly important for children who have prior positive diving experiences.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.174
Threshold uncertainty score0.193

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.115
GPT teacher head0.432
Teacher spread0.318 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations6
Published2016
Admission routes2
Has abstractyes

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