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Record W7110581599

Maternal Emotion Socialization on Children's Social Competence

2025· article· W7110581599 on OpenAlexaboutno aff

Bibliographic record

VenueJournal of the Arkansas Academy of Science · 2025
Typearticle
Language
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsnot available
Fundersnot available
KeywordsCoachingAlexithymiaEmotional competenceSocializationCompetence (human resources)Social competenceCLARITY
DOInot available

Abstract

fetched live from OpenAlex

Maternal emotion socialization plays a crucial role in children's social and emotional development (Chan et al. 2024). Previous studies have consistently shown that maternal emotion coaching is positively associated with children's social competence (Chan et al., 2024; Perkins et al., 2022; Rogers et al., 2016). However, less is known about how maternal emotional characteristics influence their emotion coaching and dismissing practices. The current study investigates whether maternal emotional clarity is associated with children's social competence through its relationship with maternal emotion coaching and dismissing behaviors. Mothers (N = 163) completed the Toronto Alexithymia Scale, Maternal Emotional Style Questionnaire, and the Early School Behavior Scale to report maternal emotional clarity, maternal emotion coaching and emotion dismissing practices, and child social competence, respectively. Structural equation modeling tested the hypothesized mediational relationships among these variables. Results indicated that mothers who had greater difficulty describing their own emotions were more likely to engage in emotion dismissing behaviors. Additionally, maternal emotion coaching was positively related to children's social competence. Interestingly, maternal emotion coaching and emotion dismissing behaviors were positively associated, suggesting that mothers who frequently use emotion coaching might simultaneously exhibit higher levels of dismissing behaviors.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.759
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
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 head0.018
GPT teacher head0.318
Teacher spread0.299 · 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.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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