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Record W2014558297 · doi:10.1108/00483480510571879

Cross‐cultural training to facilitate expatriate adjustment: it works!

2005· article· en· W2014558297 on OpenAlexaff
Marie‐France Waxin, Alexandra Panaccio

Bibliographic record

VenuePersonnel Review · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsExpatriateModerationOriginalityGermanSample (material)PsychologyValue (mathematics)Cross-culturalBusinessSocial psychologySociologyPolitical scienceHistoryStatisticsMathematicsLawAnthropology

Abstract

fetched live from OpenAlex

Purpose The paper examines what are the effects of the different types of cross‐cultural training (CCT) on expatriates' adjustment and whether prior international experience (IE) and cultural distance (CD) have a moderator effect on the effectiveness of CCT. Design/methodology/approach In a quantitative approach the paper examines the effect of four different types of CCT on the three facets of expatriates' adjustment, on a sample consisting of 54 French, 53 German, 60 Korean and 57 Scandinavian managers expatriated to India. The paper then examines the moderator effect of IE and of CD on CCT's effectiveness. Findings CCT accelerates expatriates’ adjustment. The type of CCT received matters. IE and CD have a moderator effect. Practical implications Implications for practice are identified. Originality/value The paper demonstrated the effectiveness of different kinds of CCT and the moderator effects of IE and CD.

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)0.003
metaresearch head score (Gemma)0.019
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: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.197
GPT teacher head0.410
Teacher spread0.213 · 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

Citations216
Published2005
Admission routes1
Has abstractyes

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