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Record W2016837878 · doi:10.1037/0012-1649.44.2.507

Cultural differences in the relationship between parenting and children's behavior.

2008· article· en· W2016837878 on OpenAlexafffundabout
Caroline Ho, Deborah Bluestein, Jennifer M. Jenkins

Bibliographic record

VenueDevelopmental Psychology · 2008
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsAggressionEthnic groupPsychologyDevelopmental psychologyHarshnessContext (archaeology)Multilevel modelClinical psychology

Abstract

fetched live from OpenAlex

Parent and teacher data for 14,990 children from the National Longitudinal Survey of Children and Youth were used in multilevel analyses to examine the relationship between ethnicity, children's aggression and emotional problems, and parenting. Using parent and teacher report, relationships between ethnicity and child behavior were present but modest. The association between parental harshness and child aggression differed between ethnic groups and across informants. Using teacher report of outcomes, parental harshness was positively related to child aggression in European Canadian families but negatively related in South Asian Canadian families. For all ethnic groups, parental harshness was positively related to children's aggression when parent report of outcomes was used, but relationships varied in strength across ethnic groups. The relationship of parental harshness with child emotional problems did not differ across groups, irrespective of informant. The results are discussed within the context of an ecological model of parenting.

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)0.002
metaresearch head score (Gemma)0.009
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 score0.029
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.129
GPT teacher head0.350
Teacher spread0.220 · 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

Citations143
Published2008
Admission routes3
Has abstractyes

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