Refugees and religious institutions in a mid‐size Canadian city
Bibliographic record
Abstract
Abstract Canada is a leading refugee‐settlement nation with a highly developed private refugee sponsorship programme involving many community and religious institutions. This study explored how religious institutions affect refugee settlement in Kelowna, a mid‐size city in British Columbia. Kelowna has had a significant increase in refugee sponsorship since the 2015 Syrian crisis, and most private sponsorship has involved churches and the local mosque, in collaboration with government‐funded settlement services and community partners. We collected data through a questionnaire distributed among former refugees and semi‐structured interviews with key informants including clergy, refugee‐sponsorship groups, and service providers. The results reveal that religious institutions help refugees cope with barriers and challenges in Kelowna in three main ways: bridging language barriers between newcomers, service providers, and sponsorship providers; helping newcomers establish new lives in Kelowna and move toward integration; and helping newcomers move away from precarity toward prosperity as they re‐establish themselves and their families.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.021 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".