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Record W4378422889 · doi:10.51240/jibe.2022.2.2

THE MULTIPLE DIMENSIONS OF ASIAN FACE AND THEIR IMPLICATIONS FOR ORGANIZATIONAL BEHAVIOR AND INTERNATIONAL MANAGEMENT

2022· article· en· W4378422889 on OpenAlexaff
Sang Hoon Nam

Bibliographic record

VenueJournal of International Business and Economy · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsCollectivismPhenomenonFace (sociological concept)OperationalizationSocial psychologyIndividualismHofstede's cultural dimensions theoryAffect (linguistics)SociologyPower (physics)PsychologyHonorEpistemologyPolitical scienceSocial scienceComputer scienceCommunication

Abstract

fetched live from OpenAlex

‘Face’ is a sociological concept that refers to a positive self-image that one presents or is assumed to present to others in public. Although face is considered a universal phenomenon, there are substantial cultural differences in how it is conceptualized and operationalized between collectivistic Asia and the individualistic West. Asian face is more complex and dynamic than Western face because of its multi-dimensional nature. Asians are also far more obsessed with face than Westerners are in general. I propose that the multiple dimensions of Asian face such as power/favor/relations, mask/image and moral/honor are responsible for Asian facism. I also examined how the multiple dimensions of Asian face would affect organizational behavior and international management.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0030.003
Open science0.0000.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.026
GPT teacher head0.297
Teacher spread0.271 · 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 designNot applicable
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

Citations0
Published2022
Admission routes1
Has abstractyes

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