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Record W2024782300 · doi:10.1177/0146167213481387

Agency and Facial Emotion Judgment in Context

2013· article· en· W2024782300 on OpenAlexafffund
Kenichi Ito, Takahiko Masuda, Liman Man Wai Li

Bibliographic record

VenuePersonality and Social Psychology Bulletin · 2013
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsUniversity of Alberta
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of Alberta
KeywordsPsychologyConceptualizationFacial expressionSalientAgency (philosophy)Context (archaeology)Social psychologyFace (sociological concept)Cognitive psychologyLinguisticsSociologyCommunication

Abstract

fetched live from OpenAlex

Past research showed that East Asians' belief in holism was expressed as their tendencies to include background facial emotions into the evaluation of target faces more than North Americans. However, this pattern can be interpreted as North Americans' tendency to downplay background facial emotions due to their conceptualization of facial emotion as volitional expression of internal states. Examining this alternative explanation, we investigated whether different types of contextual information produce varying degrees of effect on one's face evaluation across cultures. In three studies, European Canadians and East Asians rated the intensity of target facial emotions surrounded with either affectively salient landscape sceneries or background facial emotions. The results showed that, although affectively salient landscapes influenced the judgment of both cultural groups, only European Canadians downplayed the background facial emotions. The role of agency as differently conceptualized across cultures and multilayered systems of cultural meanings are discussed.

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)0.003
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 score0.038
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.100
GPT teacher head0.372
Teacher spread0.272 · 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

Citations50
Published2013
Admission routes2
Has abstractyes

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Same venuePersonality and Social Psychology BulletinSame topicCultural Differences and ValuesFrench-language works237,207