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Record W3110653063 · doi:10.1177/1069397120979571

Is an Emphasis on Dignity, Honor and Face more an Attribute of Individuals or of Cultural Groups?

2020· article· en· W3110653063 on OpenAlexaff
Peter B. Smith, Matthew J. Easterbrook, Yasin Koç, Vivian Miu‐Chi Lun, Dona Papastylianou, Lusine Grigoryan, Cláudio Torres, Maria Efremova, Bushra Hassan, Ammar S. Abbas, Abd Halim Ahmad, Ahmed Jalil Al-Bayati, Heyla A. Selim, Joel Anderson, Susan E. Cross, Gisela Isabel Delfino, Vladimer Lado Gamsakhurdia, Alin Gavreliuc, Dana Gavreliuc, Pelin Gül, Ceren Günsoy, Աննա Հակոբջանյան, Siugmin Lay, Olga G. Lopukhova, Ping Hu, Dıane Sunar, Maria Luisa Mendes Texeira, Doriana Tripodi, Paola Eunice Díaz Rivera, Yvette van Osch, Masaki Yuki, Natsuki Ogusu, Catherine T. Kwantes, Rolando Díaz‐Loving, Lorena R. Pérez-Floriano, Trawin Chaleeraktrakoon, Phatthanakit Chobthamkit

Bibliographic record

VenueCross-Cultural Research · 2020
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsDignityHonorSocial psychologyInterpersonal communicationNomological networkPsychologyConstrual level theorySample (material)NormativeCultural valuesPerceptionInterpersonal relationshipFace (sociological concept)SociologyStructural equation modelingSocial scienceMathematicsStatisticsEpistemologyComputer sciencePolitical science

Abstract

fetched live from OpenAlex

This study compares the individual-level and sample-level predictive utility of a measure of the cultural logics of dignity, honor, and face. University students in 29 samples from 24 nations used a simple measure to rate their perceptions of the interpersonal cultural logic characterizing their local culture. The nomological net of these measures was then explored. Key dependent measures included three different facets of independent versus interdependent self-construal, relevant attitudes and values, reported handling of actual interpersonal conflicts, and responses to normative settings. Multilevel analyses revealed both individual- and sample-level effects but the dignity measure showed more individual-level effects, whereas sample-level effects were relatively more important with the face measure. The implications of this contrast 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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.426
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.554
GPT teacher head0.581
Teacher spread0.027 · 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 teacher head, not a consensus.

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

Citations46
Published2020
Admission routes1
Has abstractyes

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