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Record W2730608836 · doi:10.1080/01494929.2017.1347549

The Examination of Emotional Facial Expressions Within Parent–Child and Sibling Interactive Contexts: A Systematic Review

2017· review· en· W2730608836 on OpenAlexaff
Isabelle Hudon-ven der Buhs, Julie Gosselin

Bibliographic record

VenueMarriage & Family Review · 2017
Typereview
Languageen
FieldPsychology
TopicEvolutionary Psychology and Human Behavior
Canadian institutionsMemorial University of NewfoundlandUniversity of Ottawa
Fundersnot available
KeywordsPsychologyFacial expressionSiblingDevelopmental psychologyEmotional expressionSocial psychologyCommunication

Abstract

fetched live from OpenAlex

This work constitutes a systematic review of the empirical literature about emotional facial expressions displayed in the context of family interaction. Searches of electronic databases from January 1990 until December 2016 generated close to 4400 articles, of which only 26 met the inclusion criteria. Evidence indicate that affective expressions were mostly examined through laboratory and naturalistic observations, within a wide range of interactive contexts in which mother–child dyads significantly outnumbered father–child dyads. Moreover, dyadic partners were found to match each others’ displays and positive and neutral facial expressions proving more frequent than negative facial expressions. Finally, researchers observed some developmental and gender differences regarding the frequency, intensity, and category of emotional displays and identified certain links among facial expression behavior, family relations, personal adjustment, and peer-related social competence.

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)0.005
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0100.009
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.149
GPT teacher head0.443
Teacher spread0.295 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations5
Published2017
Admission routes1
Has abstractyes

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