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Record W3093022294 · doi:10.1080/2331186x.2020.1830924

Cultural learning in the adjustment process of academic expatriates

2020· article· en· W3093022294 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCogent Education · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsWestern University
Fundersnot available
KeywordsExpatriatePsychologyCultural competenceCultural intelligenceFeelingCompetence (human resources)Cultural conflictSocial psychologyCultural diversityPedagogySociologySocial sciencePolitical science

Abstract

fetched live from OpenAlex

The recent rise in academic expatriates brings to the forefront the need for research to further explore this specific group of self-initiated expatriates. The purpose of this research is to study the relationship between cultural learning and adjustment of academic expatriates. Cultural learning of an academic expatriate is the strengthening and development of his/her cultural understanding, competence, and intelligence, whilst adjustment is the personal, social, and work adaptation leading to feelings of comfort towards the environment and better functioning. The main hypothesis is that increased cultural learning, which is manifested as cultural competence, is linked to well-adjusted academic expatriates. The dual theoretical framework is the theory of cultural learning and the model of cultural adjustment. The study was carried out amongst 103 academic expatriates in the UAE using quantitative methodology. The main conclusions are that: academic expatriates in the UAE are culturally competent and well adjusted; there is a positive relationship between cultural competence and adjustment in academic expatriates; cultural competence and adjustment increase with years of experience and age; expatriates from different cultural backgrounds to the host country adjust better and are more culturally competent.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.017
Threshold uncertainty score0.122

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.061
GPT teacher head0.401
Teacher spread0.340 · 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