Bibliographic record
Abstract
“Culture shock” is a common phenomenon among visitors to another country, and even the most seasoned traveler can be stymied by local behavioral norms, cultural conventions, and values. Tourists often revel in the sensation of being surrounded by the exotic and unknown. Other visitors, such as foreign exchange students, face a greater challenge as they attempt to forge relationships with native classmates and host families while learning a new language. Immigrants also face a challenge of cultural adaptation when they arrive in their new country, but they have much more at stake than the casual tourist or exchange student. Although the shock experience fades in most cases, immigrants often continue to experience difficulties reconciling the dominating cultural norms and conventions of their new home with their own norms and values. That is, the habitus of the newcomer does not match local norms and expectations. The rules of the game are defined locally, and the stranger who is unfamiliar with the rules will be unable to play effectively or will be excluded from the game altogether. Labor markets and business networks also operate according to a set of rules. For immigrants, being unfamiliar with these rules can have profound effects. For example, many Chinese business-class immigrants who came to Canada as entrepreneurs quickly discovered that the business world operates differently in Vancouver than in Hong Kong or Taipei. Many of their businesses folded and their investments flopped because they were unprepared for stringent regulations, strange business practices, and peculiar consumer behavior (Ley 1999, 2003). Consequently, a large number of Chinese immigrant entrepreneurs reoriented their investments back to China, where they knew how to run a business profitably. The return of Chinese entrepreneurs to East Asia is one of the reasons the astronaut family is a common phenomenon in Vancouver. Business regulations and conventions rendered Canada an unattractive place for investment by many Chinese immigrant entrepreneurs. In the labor market, conventions and norms are equally important. Many immigrants are unfamiliar with the norms and conventions of the hiring process in Canada, are unable to judge employers’ expectations, and are unaware of the codes of conduct in the Canadian workplace.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.010 |
| Scholarly communication | 0.019 | 0.013 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.188 | 0.109 |
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".