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Record W567965740

Young Children's Aggression: Links Between Emotion Regulation, Mother-Child Shared Affect, Parenting Practices and Parenting Support

2014· article· en· W567965740 on OpenAlexaff
Erin Romanchych

Bibliographic record

VenueScholarship at UWindsor (University of Windsor) · 2014
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsAffect (linguistics)Developmental psychologyPsychologyAggressionParenting stylesSocial psychology
DOInot available

Abstract

fetched live from OpenAlex

The present research examined links between children's emotion regulation, mother-child shared affect, mothers' perceived parenting support, parenting practices (i.e., mothers' involvement, limit setting, communication), and young children's physical aggression. Participants were 129 young children (3 to 6 years) and their mothers. Mothers completed questionnaires assessing parenting practices, parenting support, and their children's emotion regulation and aggressive behaviour. Mother-child dyads participated in a free play task and a structured block task. These mother-child interactive tasks were coded for shared positive and negative affect between the dyads. Higher levels of mothers' limit setting and communication were each related to lower levels of children's physical aggression. Higher levels of mothers' involvement, and limit setting were related to lower levels of children's physical aggression, partially because children were better at regulating their emotions. These findings are discussed with regards to implications for working with aggressive young children and their parents.

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)0.003
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 score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
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 science0.0000.000
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 head0.025
GPT teacher head0.266
Teacher spread0.241 · 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

Citations8
Published2014
Admission routes1
Has abstractyes

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