Resettlement, Employment, and Mental Health Among Syrian Refugee Men in Canada: An Intersectional Study Using Photovoice
Bibliographic record
Abstract
CONTEXT: The impact of forced migration on the mental health of refugee men is far-reaching and compounded by gendered masculinity, which shapes men's access to employment and other resources. A gap in knowledge exists on the broader determinants of refugee men's mental health. METHODOLOGY: = 11) Syrian refugee men in the Canadian context. Theoretical approaches of intersectionality and masculinity were applied to understand how power relations shape Syrian men's identities, their access to employment, and impacts on their mental health. ANALYSIS AND RESULTS: Syrian men's identities were marginalized by working in low-wage jobs because of inequitable policies that favored Canadian experience and credentialing assessment processes that devalued their knowledge. Multiple and overlapping factors shaped Syrian men's mental health including language and literacy barriers, time and stage of life, isolation and loneliness, belonging and identity, and gender-based stress. Caring masculinities performed through fathering, cultural connection, and service-based work promoted agency, hope, and resilience. CONCLUSIONS: Public health and community-based pathways must adopt gender-responsive and intersectional approaches to policy and practice. Peer-based programs may mitigate harmful forms of masculinity and promote transformative change to support refugee men's mental health.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.016 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".