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Record W2125650272 · doi:10.1080/09585190802670524

Expatriate adjustment from the inside out: an autoethnographic account

2009· article· en· W2125650272 on OpenAlexaff
Perley-Ann Friedman, Lorraine Dyke, Steven A. Murphy

Bibliographic record

VenueThe International Journal of Human Resource Management · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsCarleton University
Fundersnot available
KeywordsExpatriateShock (circulatory)SociologyWork (physics)Process (computing)PsychologyManagementSocial psychologyEconomicsPolitical scienceComputer scienceLawEngineering

Abstract

fetched live from OpenAlex

This paper identifies some of the dynamics of expatriate adjustment using an autoethnographic account of situations experienced by the first author during her first year of work at a financial services company in Hong Kong. Success in this cross-cultural assignment is dependent on the expatriate's ability to adjust to and master the new culture. Our theoretical analysis of the autoethnographic account suggests that culture shock may be a discontinuous process. Further, the analysis suggests that cultural acceptance can play a critical role in expatriate adjustment.

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)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.007
Scholarly communication0.0040.005
Open science0.0010.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.048
GPT teacher head0.352
Teacher spread0.304 · 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 designQualitative
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

Citations50
Published2009
Admission routes1
Has abstractyes

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