Intercultural adjustment challenges of Korean and Canadian self-initiated expatriates in the workplace: An exploratory bidirectional investigation
Bibliographic record
Abstract
This study uses a qualitative approach and bidirectional design to explore the unique intercultural adjustment challenges that Korean and Canadian self-initiated expatriates (SIEs) experience in each other’s workplace. Through semi-structured interviews we draw upon thematic analysis to surface unique cross-cultural challenges finding that a ‘one-size’ fits all approach to understanding SIE adjustment is overly simplified and omits contextual considerations. Canadian SIEs struggled with issues related to power distance, collectivism and communication styles, whereas language barriers, individualism and hierarchical differences were major challenges for Korean SIEs. We apply our findings to previous conceptual models of cross-cultural adjustment and discuss three criteria: size of cultural gap, direction of immigration and unique contextual factors as necessary for understanding the intricate dynamics of SIE and host-country national relationships. Implications and limitations of this study are followed by recommendations for future research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".