Stress, Coping, and Religiosity among Recent Syrian Refugees in Canada
Bibliographic record
Abstract
As of November 2015, 34 696 Syrian refugees have resettled in Canada (Government of Canada, 2016). Previous studies with refugee populations have found: a) depression, anxiety, and posttraumatic stress disorder resulting from trauma in their country of origin; and b) problems with discrimination and Islamophobia in new host cultures. Thus, coping strategies have been crucial for refugees to thrive in their new host countries. The current study conducted qualitative interviews with 10 recently arrived Muslim, Arab, Syrian refugees in Windsor, Ontario. The interviews explored participants’ pre- and post-arrival experiences in Syria and Canada. The interviews were recorded, transcribed, and coded using an interpretive phenomenological analysis (IPA) approach, into themes that emerged from refugees' lived experiences. Themes were organized based on the Transactional Model of Cultural Stress and Coping (Chun, Moos, & Cronkite, 2006). The results revealed superordinate themes that corresponded to each of the panels within the theoretical framework. The superordinate themes included 1) pre-migration stress and trauma; 2) identity assertion; 3) post-migration stressors; 4) religious and collective coping; and 5) positive outcomes and well-being in Canada. Pre-migration stress and trauma entailed fear for safety of family members, discrimination from citizens of neighbouring countries, and financial instability. Through enduring adversity, Syrian refugees asserted cultural and religious identities as well as their gender identities. Post-migration experiences included stressors in the form of acculturative stress, discrimination, financial burden, and survivor’s guilt and loss. To cope, Syrian refugee participants reported the use of religious coping and collective coping strategies to ultimately achieve positive outcomes and hopeful outlooks for their future in Canada. The findings expanded on existing literature on stress and coping, and illuminated the importance of the cultural and religious contexts of Muslim Syrian refugees in Canada.
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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 | 0.002 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.002 | 0.000 |
| 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".