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Record W1990147200 · doi:10.5993/ajhb.28.5.2

Neighborhood, Family, and Child Predictors of Childhood Injury in Canada

2004· article· en· W1990147200 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAmerican Journal of Health Behavior · 2004
Typearticle
Languageen
FieldMedicine
TopicInjury Epidemiology and Prevention
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsDisadvantageLogistic regressionLongitudinal studyAffect (linguistics)Injury preventionEarly childhoodPsychologyDevelopmental psychologyDemographyPoison controlHuman factors and ergonomicsMedicineEnvironmental healthSociologyPolitical science

Abstract

fetched live from OpenAlex

OBJECTIVE: To examine independent and combined effects of child, family and neighborhood on medically attended childhood injuries. METHODS: Logistic modeling of longitudinal data (n=9796) from the Census Linked National Longitudinal Survey of Children and Youth. RESULTS: Child age and gender were strong predictors of injuries. Smaller effects were found for parenting, neighborhood cohesion among difficult children less than 2 years old, and neighborhood disadvantage among aggressive children 2-3 years old. CONCLUSION: Neighborhood in addition to parenting can affect injury risk. Further research is needed into the influence of neighborhood disadvantage and the processes of neighbor's cohesion at different childhood stages.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.310
Threshold uncertainty score0.979

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.009
GPT teacher head0.300
Teacher spread0.290 · 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