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Record W1990467542 · doi:10.1037/a0016300

Smile intensity and warm touch as thin slices of child and family affective style.

2009· article· en· W1990467542 on OpenAlexaff
Christopher Oveis, June Gruber, Dacher Keltner, Juliet L. Stamper, W. Thomas Boyce

Bibliographic record

VenueEmotion · 2009
Typearticle
Languageen
FieldPsychology
TopicEvolutionary Psychology and Human Behavior
Canadian institutionsLearning PartnershipUniversity of British Columbia
FundersNational Institute of Mental Health
KeywordsPsychologyStyle (visual arts)Extraversion and introversionPersonalityDevelopmental psychologyFacial expressionBig Five personality traitsSocial psychologyCommunication

Abstract

fetched live from OpenAlex

The authors investigate the claim that thin slices of expressive behavior serve as reliable indicators of affective style in children and their families. Using photographs, the authors assessed smile intensity and tactile contact in kindergartners and their families. Consistent with claims that smiling and touch communicate positive emotion, measures of children's smile intensity and warm family touch were correlated across classroom and family contexts. Consistent with studies of parent-child personality associations, parents' warm smiles and negative facial displays resembled those of their children. Finally, consistent with observed relations between adult personality and positive display, children's smiling behavior in the classroom correlated with parent ratings of children's Extraversion/Surgency. These results highlight the utility of thin slices of smiling and touch as indicators of child and family affective style.

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)0.000
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.018
GPT teacher head0.305
Teacher spread0.287 · 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

Citations55
Published2009
Admission routes1
Has abstractyes

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