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Record W2003867830 · doi:10.1080/03004430903415023

Narrative structure and emotional references in parent–child reminiscing: associations with child gender, temperament, and the quality of parent–child interactions

2010· article· en· W2003867830 on OpenAlexfundno aff
Kelly K. Bost, Eunsil Choi, Maria S. Wong

Bibliographic record

VenueEarly Child Development and Care · 2010
Typearticle
Languageen
FieldPsychology
TopicIdentity, Memory, and Therapy
Canadian institutionsnot available
FundersUniversity of British ColumbiaUniversity of UtahNational Science Foundation
KeywordsTemperamentIntrusivenessHostilityPsychologyDevelopmental psychologyNarrativePersonalityClinical psychologySocial psychology

Abstract

fetched live from OpenAlex

The present research examined child gender, temperament, and the quality of parent–child interactions as predictors of narrative style and references to emotion during mother–child and father–child reminiscing. Although models predicting parents' narrative styles were non‐significant, results revealed significant interactions between parental hostility/intrusiveness during an interaction task and difficult child temperament. For mothers, greater hostility/intrusiveness was associated with fewer emotional references, but only when perceived difficult temperament was high. For fathers, greater hostility/intrusiveness was associated with more emotional references, but only when perceived difficult temperament was high. Additionally, greater paternal supportive guidance was associated with more references to positive emotions for fathers. No child gender effects were found to be significant.

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 score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.033
GPT teacher head0.323
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

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

Citations14
Published2010
Admission routes1
Has abstractyes

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