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Record W2134944883 · doi:10.1111/jomf.12192

Father Involvement and Childhood Injuries

2015· article· en· W2134944883 on OpenAlexaboutno aff
Lenna Nepomnyaschy, Louis Donnelly

Bibliographic record

VenueJournal of Marriage and the Family · 2015
Typearticle
Languageen
FieldMedicine
TopicInjury Epidemiology and Prevention
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Fragile Families and Child Wellbeing StudyPsychologyInjury preventionDevelopmental psychologyDiversity (politics)Suicide preventionHuman factors and ergonomicsDemographyPoison controlMedicineMedical emergencyGeography

Abstract

fetched live from OpenAlex

Abstract Unintentional injury is the leading cause of death for children in the United States. Parental supervision is a key factor in preventing injuries, but little is known about the role of fathers. Today, one quarter of children live with a single mother, and another third live with a mother and her new partner, resulting in tremendous diversity in the amount and type of paternal involvement in children's lives. The authors examined the effects of involvement by resident biological, nonresident biological, and resident social fathers on the risk of injury among children from birth to age 5 using data from the Fragile Families and Child Wellbeing Study (N = 4,352). They found that living with a social father and social fathers' more frequent engagement with children increase risk of injury, but only for the youngest children. Higher levels of fathers' cooperative parenting reduce children's risk of injury regardless of fathers' biological or residential status.

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)0.006
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 score0.012
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.025
GPT teacher head0.285
Teacher spread0.261 · 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

Citations15
Published2015
Admission routes1
Has abstractyes

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