Mental health challenges of recent immigrants in precarious work environments — a qualitative study
Bibliographic record
Abstract
Introduction: Recent immigrants from racialized minority backgrounds and those who are not proficient in the local language are some of the most vulnerable members of society. Despite having postsecondary educational qualifications and permanent residency status, many are engaged in precarious employment. There is a scarcity of research that has explicitly focused on the work experiences and mental health challenges faced by these immigrants. Methods: Using a grounded theory approach and semi-structured face-to-face interviews, this study examined the work experiences and mental health challenges of 42 recent immigrant employees from two cities in Canada who were working in various industries and engaged in precarious employment. Findings: Eighty-one percent of the employee participants were overqualified for their jobs. Findings highlighted several ongoing mental problems that participants experienced, stemming from challenging physical and psychological workplace conditions, negative mindsets associated with their recent immigrant status, and other contextual factors and barriers. However, various coping strategies, both constructive and unconstructive, were used to address this mental distress. Discussion: The study proposes a multidimensional approach to address workplace conditions to promote good mental health for these employees. This includes preventative programs for raising awareness among employers about the importance of recent immigrant employees' mental health and well-being and policy and legislation changes to ensure the employer's commitment to creating a safe and culturally friendly workplace. The approach also recommends that recent immigrant employees receive occupational health and safety training, learn about Canadian workplace norms and culture, and have access to professional healthcare services.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".