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Who I Am Depends on How I Feel

2009· article· en· W2140381495 on OpenAlexaff
Claire E. Ashton‐James, William W. Maddux, Adam D. Galinsky, Tanya L. Chartrand

Bibliographic record

VenuePsychological Science · 2009
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAffect (linguistics)PsychologySocial psychologyConformityExpression (computer science)NormativePreferenceDevelopmental psychologyInterdependenceCultural group selectionCultural diversityEthnic group

Abstract

fetched live from OpenAlex

We present a novel role of affect in the expression of culture. Four experiments tested whether individuals' affective states moderate the expression of culturally normative cognitions and behaviors. We consistently found that value expressions, self-construals, and behaviors were less consistent with cultural norms when individuals were experiencing positive rather than negative affect. Positive affect allowed individuals to explore novel thoughts and behaviors that departed from cultural constraints, whereas negative affect bound people to cultural norms. As a result, when Westerners experienced positive rather than negative affect, they valued self-expression less, showed a greater preference for objects that reflected conformity, viewed the self in more interdependent terms, and sat closer to other people. East Asians showed the reverse pattern for each of these measures, valuing and expressing individuality and independence more when experiencing positive than when experiencing negative affect. The results suggest that affect serves an important functional purpose of attuning individuals more or less closely to their cultural heritage.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.003

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 head0.156
GPT teacher head0.449
Teacher spread0.293 · 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

Citations34
Published2009
Admission routes1
Has abstractyes

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