Language Use and Attitudes Among Ukrainian Refugees in Canada: Do They Differ by Participants’ Age?
Bibliographic record
Abstract
The language use of Ukrainian war refugees has attracted the attention of researchers worldwide due to the unprecedented number of individuals displaced since the onset of the war in 2022. Earlier studies have documented a shift in language use and attitudes in Ukraine, marked by a diminished role for Russian and increased prominence of Ukrainian both within the country and among Ukrainian émigré communities abroad. However, the role of age in this process has not yet been thoroughly investigated. Moreover, research on the specific characteristics of language shift and social integration among Ukrainian refugees in Canada is still insufficient. This article reports the results of a study aimed at examining how home languages shift and the use of the official languages among Ukrainian refugees in Canada may vary by age. The vresearch employed a mixed-methods approach, based on a survey (65 participants). In this research, quantitative data were drawn from the closed-ended survey questions, and open-ended questions were employed to illustrate quantitative results for more depth and insight. The results indicate that there are no significant differences in L1 and L2 or L3 by age in this sample. The study confirms a language shift from Ukrainian-Russian bilingualism in Ukraine to Ukrainian dominance, which does not differ by age or age group. What does differ by age and generation is the proficiency in English, English use, and the perceived difficulty in learning English, whereby younger participants reported higher proficiency in English, its higher use in daily communication, and less difficulty acquiring it, as compared to their older peers. While the findings align with previous research on language use among immigrants—including the impact of age—they offer new insights into the experiences of refugees, highlighting how different age groups respond to social pressures in migration. A further contribution of this study lies in addressing the language shift from the perspectives of both younger and older refugees and establishing that the language shift in Ukraine swept across all ages.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".