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Psychological Distance and Culture

2019· book-chapter· en· W3006742519 on OpenAlexaff
Michael Roberts

Bibliographic record

VenueAdvances in marketing, customer relationship management, and e-services book series · 2019
Typebook-chapter
Languageen
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsMount Royal University
Fundersnot available
KeywordsConceptualizationConstrual level theoryHofstede's cultural dimensions theoryPsychologySocial distanceSocial psychologyTacit knowledgeSociologySpace (punctuation)EpistemologyKnowledge managementComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

This chapter introduces psychological distance into cultural studies as an alternative way of conceptualizing individual differences. Unlike most cross-cultural frameworks that are at the group level, psychological distance provides an individual level conceptualization of distance. This conceptualization can complement the more group level and static frameworks that dominate management theory. The framework is rooted in knowledge theory. By developing the concepts of socially embedded tacit vs. explicit knowledge, the chapter demonstrates that explicit models of cultural difference, such as Hoftsede's Cultural Dimensions, do not capture the lived tacit experience of managers working in a cross-cultural setting. This chapter is conceptual, but the framework that is developed here emerged from fieldwork conducted by the author on returnee executives in Korea. Psychological distance consists of four dimensions: time, space, social relations, and probability. These dimensions relate to the level of mental construal between an individual and a foreign knowledge practice.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.007
Scholarly communication0.0070.006
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0120.001

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 head0.016
GPT teacher head0.309
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 designTheoretical or conceptual
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
Published2019
Admission routes1
Has abstractyes

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