Bibliographic record
Abstract
This is an accepted article with a DOI pre-assigned that is not yet published.Introduction: Studieshave documented on the role of religious leaders in providing psychosocial supportto their members. However, there is a dearth of research in understanding therole imams play among Muslim communities in the Canadian context. The fewstudies undertaken in Europe and the United States revealed that imams play asignificant role in addressing the psychosocial needs of their congregants andthis role increased in post 9/11 era.Objectives: This study explored experiences of imams in theprovision of psychosocial support to Muslim Canadians including new immigrantsand refugees. Methods: In-depth 1:1 interviews with faith leaders ina major metropolitan Canadian city was done. The data was transcribed andthematically analyzed using NVIVO. Results: The study revealed that spiritual healing isconsidered as first line of care for psychosocial illness, and, imams areconsidered as the primary support network. The findings revealed that war-relatedtraumas and post-resettlement challenges have significant impact on familyfunctions and wellbeing. Conclusion: Thisstudy highlighted the need for culturally appropriate psychosocial supportservices for Muslim Canadians including new immigrants and refugees. It also calls for better collaborationbetween service agencies and faith-based organizations in the communities toaddress these specific needs.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.888 | 0.765 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".