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Family Talk about Internal States and Children's Relative Appraisals of Self and Sibling

2008· article· en· W2001491218 on OpenAlexafffund
Holly Recchia, Nina Howe

Bibliographic record

VenueSocial Development · 2008
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of CanadaSociety for Research in Child Development
KeywordsSiblingPsychologyDevelopmental psychologySibling relationshipPerspective (graphical)Social psychology

Abstract

fetched live from OpenAlex

Abstract This study investigated associations between preschoolers' conversations about internal states and their spontaneous appraisals of self and sibling. Thirty‐two preschoolers (M age = 3.9 years) were observed during naturalistic home interactions with mothers and younger siblings. Various features of mothers' and children's internal state language were coded. Children who talked about internal states to the baby and who talked more about the baby's perspective tended to appraise their sibling negatively relative to self. In contrast, mothers' references to internal states, as well as their promotion and encouragement of the child's own internal state talk, were negatively related to the differences between children's negative appraisals of self and sibling. These results support the social‐constructivist notion that the quality of children's interactions with family members is related to how they construe themselves in comparison to their siblings.

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 score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.050
GPT teacher head0.335
Teacher spread0.285 · 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

Citations20
Published2008
Admission routes2
Has abstractyes

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