Investigating Chinese Migrants' Information-Seeking Patterns in Canada: Media Selection and Language Preference
Bibliographic record
Abstract
Taking a quantitative approach, this research surveyed Chinese migrants in Canada regarding channels they rely on to seek various information. This research also investigates how Chinese migrants’ preferences of channels correlate with their intercultural sensitivity level. Chinese migrants prefer Chinese newspapers and websites for government/policy information and life information rather than English newspapers and websites. However, they use English newspapers and websites more frequently for job and career development information. Overall, English television and radio are more frequently used by Chinese migrants than Chinese television and radio broadcasts. The intercultural sensitivity levels of Chinese migrants have a positive correlation with their frequencies of using English information resources, including government websites, English newspapers, English non-government websites, government officers, personal non-Chinese social networks, and English television and radio. Findings of this research suggest that Chinese ethnic media play an important role in Chinese migrants’ information-seeking behaviours and patterns in Canada. On one hand, government and other organizations can reach the Chinese migrant community through information diffusion in Chinese ethnic media. On the other hand, Chinese migrants should make an active effort to improve their English proficiency and intercultural communication sensitivity to better integrate themselves into the Canadian society. A more balanced approach of seeking information from English and Chinese media sources could be more beneficial for Chinese migrants.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".