Language Acquisition, Mental Health, and Acculturation among Migrants in Canada
Bibliographic record
Abstract
This dissertation examines the integration of first-generation migrants in Canada, focusing on the constructs of acculturation, language proficiency, and mental health. With nearly a quarter of Canada's population comprising migrants (Statistics Canada, 2022), understanding their adjustment is critical. Acculturation, language proficiency, and mental health can all have an impact on the success of migrants in their new country (Balidemaj et al. 2019; Brance et al. 2023; Iversen et al. 2014; Rousseau et al. 2019; Rashtchi et al. 2012; Salami et al. 2019). There are a limited number of studies examining these variables in relation to certain migrant groups, such as refugees within the Canadian context (Maehler, 2021). This dissertation intends to extend our knowledge of relations among mental health, acculturation and language proficiency through four studies. Study 1 examined newcomer migrants' demographics, mental health, and language acquisition compared to those of the Canadian-born population. This study uses two large datasets to underscore the significance of language proficiency in shaping health trajectories. Study 2 narrowed the focus on Iranian immigrants as a specific ethnic group. This study revealed the important associations between acculturation strategies and first-generation immigrants’ mental health. Studies 3 (Time 1) and 3 (Time 2) further examined the relationships among mental health, language acquisition, and acculturation among first-generation immigrants. Findings indicate that while examining the large datasets, duration of residence shows some associations with mental health effects, but the effect size is very small. A more focused examination of these variables facilitated by Study 2 and Study 3 (Time 1 and Time 2) revealed that acculturation strategies and language proficiency significantly influence mental health, while the length of stay in Canada is not associated with mental health outcomes when other variables are included. The results derived from both standardized measures and interviews revealed that an integrative acculturation strategy is associated with better mental health outcomes. The findings from this dissertation advocate for policies that support bi-cultural identity, maintaining heritage culture appears beneficial for adjustment and well-being. Acquiring the mainstream culture may increase awareness of mental health resources, discover paths to receive treatment, and communicate mental health needs. The results underscore the importance of continued, diverse longitudinal research to enrich the understanding of immigrants’ experiences. Further implications for each study are discussed.
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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 | 0.003 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".