The linguistic Odyssey of Russian-speaking immigrants in Canada
Bibliographic record
Abstract
Aims and objectives/purpose/research questions: Very little is known to date about the long-term dynamics of balancing home and dominant languages by adult immigrants. Russian-speaking immigrants in Canada remain an underrepresented group with no available studies of their language development. To address these gaps, this article describes a linguistic journey experienced by Russian-speaking immigrants in Canada as they adapt to the life in the host country. The major objective of the study is to examine the importance of learning the host country’s majority languages (English and French) vis-à-vis maintenance of the home language as seen by the participants in the beginning and after a few years of immigration. Design/methodology/approach: The article reports the results of a mixed-methods study involving an online survey and written narratives about language dynamics in immigration. Data and analysis: One hundred Russian-speaking immigrants from nine countries residing in seven Canadian provinces participated in the study. The analysis involves quantitative comparisons of responses involving correlation and chi-square tests as well as qualitative descriptions of the participants’ linguistic experiences. Findings/conclusions: The results indicate that over the time since immigration, the importance of the English language learning decreases, and the importance of Russian language maintenance increases for the participants, whereas the salience of acquiring French remains unchanged. Originality: The new finding is the trajectory of the relationship between the participants’ interest in the home language and culture maintenance and host languages and cultures learning over the years of immigration. Significance/implications: These results align with the authors’ linguistic equilibrium hypothesis of language dynamics in immigration. The implications of the study involve long-term support of linguacultural needs of immigrant communities. Limitations: The research conducted during COVID-19 was limited in methods and would benefit from in-person interviews in future. Expanding the project to other immigrant groups for comparison is another direction for future research.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.004 |
| 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".