The health of foreign-born homeless families living in the family shelter system
Bibliographic record
Abstract
Purpose Foreign-born families face challenges following migration to Canada that may impact their well-being and lead them to homelessness. Yet, there is limited research on the experience of homelessness in this population. The purpose of this paper is to examine the health of foreign-born families staying in the emergency shelter system in Ottawa, Ontario, Canada, and compare their experiences to Canadian-born homeless families who are also living in shelters. Design/methodology/approach Interviews were conducted with 75 adult heads of families who were residing in three family shelters. This study focused on mental and physical health functioning, chronic medical conditions, access to care and diagnoses of mental disorders. Findings Foreign-born heads of families reported better mental health than did Canadian-born heads of families with a significantly lower proportion of foreign-born participants reporting having been diagnosed with a mental disorder. Foreign-born heads of families also reported fewer chronic medical conditions than did Canadian-born heads of families. Research limitations/implications This study relied on self-reported health and access to healthcare services. Data were drawn from a small, non-random sample. Originality/value This study is one of the first studies to examine the health and well-being of homeless foreign-born heads of families. Moreover, this paper also focuses on disparities in health, diagnoses of mental disorders, and access to healthcare services between foreign-born and Canadian-born families – a comparison that has not been captured in the existing literature.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".