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Record W2119842506 · doi:10.3390/ijerph9083002

Dog Bite Risk: An Assessment of Child Temperament and Child-Dog Interactions

2012· article· en· W2119842506 on OpenAlexaff
Aaron L. Davis, David C. Schwebel, Barbara A. Morrongiello, Julia Stewart, Melissa Bell

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsTemperamentImpulsivityPsychologyPsychological interventionObservational studyShynessInjury preventionPoison controlDevelopmental psychologyClinical psychologyIntervention (counseling)Human factors and ergonomicsSuicide preventionMedicinePediatricsAnxietyPersonalityPsychiatryEnvironmental healthSocial psychology

Abstract

fetched live from OpenAlex

Annually approximately 400,000 American children receive treatment for dog bites. Young children are at greatest risk and are frequently bitten following behavior that provokes familiar dogs. This study investigated the effects of child temperament on children's interaction with dogs. Eighty-eight children aged 3.5-6 years interacted with a live dog. Dog and child behaviors were assessed through observational coding. Four child temperament constructs-impulsivity, inhibitory control, approach and shyness-were assessed via the parent-report Children's Behavioral Questionnaire. Less shy children took greater risks with the dog, even after controlling for child and dog characteristics. No other temperament traits were associated with risk-taking with the dog. Based on these results, children's behavior with unfamiliar dogs may parallel behavior with other novel or uncertain situations. Implications for dog bite intervention programs include targeting at-risk children and merging child- and parent-oriented interventions with existing programs geared toward the physical environment and the dog.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.055
GPT teacher head0.480
Teacher spread0.425 · 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 source (direct Gemma or distilled Codex), 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

Citations55
Published2012
Admission routes1
Has abstractyes

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