The Linguistic Journey of Russian-Speaking Immigrants in Canada
Bibliographic record
Abstract
Immigration to a new country begins with a process of adapting into a new society which is also known as acculturation (Berry, 1997). The study focuses on one type of integration strategy described by Berry (1997) strategies as the bidimensional model of acculturation, which refers to an orientation to support both home and host cultures. The number of Russian-speaking immigrants in Canada is growing (Statistics Canada, 2011; Statistics Canada, 2016). However, relatively few studies have explored the experiences of this particular immigrant population. The present research aims to describe the linguistic journey of Russian-speaking immigrants, particularly the connections between the language use by Russian-speaking immigrants and an acculturation process experienced by them after moving to Canada. Specifically, it examines the ways that Russian-speaking immigrants adapt to Canadian society, learn English and French, and at the same time maintain the culture of their home country and preserve the Russian language. My findings are based on the responses of 100 Russian-speaking immigrants from seven provinces in Canada who took part in an online questionnaire which contained questions about linguistic use and preferences, adaptation process, and immigration experience. The data were analyzed using Chi-square test and Pearson correlation. The study shows that the surveyed Russian-speaking immigrants can successfully balance between supporting both cultures and languages. The results also demonstrate that the importance of English / French learning and maintenance of Russian among participants changes over time, with priority shifting from learning English to maintaining Russian. Actions that can help to ease adaptation include the active use of the official languages, learning the history and cultural aspects of Canada, and the use of local media. The home culture can be maintained by using the Russian language more, having Russian-speaking friends, reading books and watching movies in Russian. The present study expands the acculturation theory of Russian-speaking immigrants in Canada and can be used in creating a better environment for newcomers.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.018 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".