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Record W1993241726 · doi:10.1017/s0954579408000059

Young children's representations of conflict and distress: A longitudinal study of boys and girls with disruptive behavior problems

2008· article· en· W1993241726 on OpenAlexaff
Carolyn Zahn‐Waxler, Jong-Hyo Park, Barbara A. Usher, Francesca Belouad, Pamela M. Cole, Reut Gruber

Bibliographic record

VenueDevelopment and Psychopathology · 2008
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsMcGill University
FundersNational Institutes of Health
KeywordsPsychologyAggressionProsocial behaviorAngerDevelopmental psychologyDistressConduct disorderNarrativeClinical psychology

Abstract

fetched live from OpenAlex

We investigated narratives, symbolic play, and emotions in children who varied in severity of disruptive behavior problems. Children's representations of hypothetical situations of conflict and distress were assessed at 4-5 and 7 years. Behavior problems also were assessed then and again at 9 years. Children's aggressive and caring themes differentiated nonproblem children, children whose problems remained or worsened with age, and those whose problems improved over time. Differences in boys and girls whose problems continued sometimes reflected exaggerations of prototypic gender differences seen across the groups. Boys with problems showed more hostile themes (physical aggression and anger), whereas girls with problems showed more caring (prosocial) themes relative to the other groups. Modulated (verbal) aggression, more common in girls than boys, showed developmentally appropriate increases with age. However, this was true only for children without problems and those whose problems improved. We consider how these findings contribute to an understanding the inner worlds of boys and girls who differ in their early developmental trajectories for behavior problems.

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)0.004
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 score0.035
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.002
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 head0.039
GPT teacher head0.304
Teacher spread0.266 · 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

Citations62
Published2008
Admission routes1
Has abstractyes

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