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Record W2004547500 · doi:10.1177/0165025414535121

Canadian portrait of changes in family structure and preschool children’s behavioral outcomes

2014· article· en· W2004547500 on OpenAlexaffabout
Julie Gosselin, Elisa Romano, Tessa Bell, Lyzon Babchishin, Isabelle Hudon-ven der Buhs, Annie Gagné, Natasha Gosselin

Bibliographic record

VenueInternational Journal of Behavioral Development · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicFamily Dynamics and Relationships
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPsychologyAggressionDevelopmental psychologyLongitudinal studyImpulsivityMedicine

Abstract

fetched live from OpenAlex

Whereas US-based data have contributed to our understanding of family composition changes over the last decades, data on Canadian families are limited, and previous studies have stressed the need for in depth, longitudinal investigations. This article begins to fill this gap in the literature by providing a current and detailed portrait of family composition changes from 1996 to 2008 (Study 1). Additionally, we performed an analysis of the role of specific child, parent and family characteristics, in interaction with family composition and family transition, in predicting pre-school children’s behavioral outcomes (Study 2). Using nationally-representative Canadian data collected from the National Longitudinal Survey of Children and Youth (NLSCY), we focus our inquiry on a mean sample for 0–5-year-olds of 2,866 children at cycle 8 (2008). Results show increases in non-traditional family households over time, as well as significant relationships between child characteristics, household characteristics, and family processes in predicting three behavioral outcomes: emotional problems, hyperactivity/impulsivity, and physical aggression.

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)0.000
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 score0.394
Threshold uncertainty score0.950

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.021
GPT teacher head0.309
Teacher spread0.289 · 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

Citations7
Published2014
Admission routes2
Has abstractyes

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