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Record W4324025877 · doi:10.1177/0192513x231162965

Exploring Linkages Between Mother–Child and Sibling Relationship Quality and Prosocial Behavior Between School-Aged and Adolescent Siblings

2023· article· en· W4324025877 on OpenAlexafffund
Caroline C. Piotrowski

Bibliographic record

VenueJournal of Family Issues · 2023
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversity of Manitoba
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsProsocial behaviorSiblingSibling relationshipDevelopmental psychologyPsychologyNegativity effect

Abstract

fetched live from OpenAlex

The present study investigated the degree to which the quality of sibling relationships interacted with the quality of mother-child relationships to concurrently predict prosocial behavior between school-aged siblings while taking age spacing into account. Forty-five families with two school-aged siblings were recruited from the community. Prosocial behavior was coded from unstructured laboratory observation of sibling interaction. Both children reported on the quality of their sibling relationships; the quality of mother-child relationships was assessed by coding laboratory observation of mother-child interaction, conducted separately with each sibling. A compensatory pattern was found; higher warmth between widely spaced siblings was associated with greater sibling prosocial behavior when maternal positivity was low, and also when maternal negativity was high. These compensatory patterns did not occur for siblings closer in age. Findings suggested that sibling dynamics and relational roles play an important function in children's prosocial development. Results were discussed within family systems frameworks.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.009
Threshold uncertainty score0.704

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.331
GPT teacher head0.413
Teacher spread0.081 · 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.

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

Citations3
Published2023
Admission routes2
Has abstractyes

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