Culture Shock Experiences: A Case Study of a Canadian in Vietnam
Bibliographic record
Abstract
Culture shock has always been an important issue.Previous studies on the cultural adaptation process have only focused on the general nature of culture shock.Yet, little attention has been drawn to how expatriates from Englishspeaking countries have undergone culture shock in Vietnam.This paper presents a case study of a native Canadian who had settled in Vietnam for 11 years (up to the time of the study).The study aimed to investigate the aspects of the participant's cultural experience, the factors determining its severity, and the strategies to facilitate the adaptation process.The research involved a case study approach using a semi-structured interview as a main data collection instrument.The findings reveal that (1) five aspects of culture shock were learning the Vietnamese language, joining a close community, detecting smells, using transportation, and observing local behaviors; (2) the factors determining the intensity levels of culture shock included language barriers, communities, personality traits and different regions in Vietnam, while previous overseas experiences had less impact; and (3) to overcome the culture shock, the participant learned the Vietnamese language, made friends with the locals, remained disciplined and kept himself occupied.The findings of this cultural phenomenon could provide helpful insights to English teachers and students interested in language and culture studies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.037 | 0.006 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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 source (direct Gemma or distilled Codex), 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".