Mental Illness Through the Eyes of Iraqi Ontarians: Unheard Voices for Conventional Mental Health Supports
Bibliographic record
Abstract
While the influx of Middle Eastern migrant groups continues to grow around the world, displaced Iraqis make up a significant portion of this inflow as they flee Iraq’s internal conflict and corruption, leaving behind political, economic, and environmental disparities. The 2011 National Household Survey found that Canada is home to 49,680 Iraqis, with more than 37,000 refugees who arrived between 2003 and 2018. The author conducted an exploratory qualitative research study to explain the perceptions of mental illness among Iraqi migrant groups in Ontario, Canada. Utilizing critical realism as the philosophical framework for this study, the author used a combination of theoretical frameworks that best describe the dominant views of mental illness in the West, along with the dominant views that shape perceptions of mental illness in the Middle East. The author recruited a convenience sample of 15 Iraqi participants across Ontario and interviewed them using five structured interview questions to explore how Iraqi migrants understand and perceive mental health and mental illness, their relationship with mental health service providers, and the involvement of religion in receiving mental health and mental illness support. The researcher employed content analysis analytic design to complete this study. Results from the study show that Iraqi migrants already understand mental illness, however, their understanding is aligned with the religious and cultural expectations they were raised upon in the Middle East.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.024 | 0.025 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".