Sleeping on the margins : the role of social capital in the housing patterns of refugee claimants in the Greater Vancouver Regional District
Bibliographic record
Abstract
Immigrants, especially those who are visible minorities, are at a socio-economic disadvantage upon arrival relative to their Canadian-born counterparts. Refugee claimants face additional barriers upon arrival owing to their specific mode of entry. These compounded obstacles hamper the search for safe and affordable housing for claimants, and places them at a high risk of relative homelessness. This thesis examines the housing patterns of refugee claimants in the Greater Vancouver Regional District (GVRD) by analyzing the residential trajectories of thirty-six refugee claimants. I, furthermore, analyze the recent literature that focuses on the settlement patterns of claimants in Montreal, Toronto and Vancouver in order to facilitate a wider discussion on the settlement needs of this particular group. In so doing, I explore various themes, such as affordability, adequacy and safety, which are consistent issues for claimants across Canada. This thesis argues that for many claimants, hidden homelessness is an inevitable part of their settlement. This study moves forward to question why, given their socioeconomic disadvantage over the average Canadian-born and other immigrants, are claimants not finding themselves in absolute homelessness -living on the streets or in shelter system? In order to assess this, I examine theories of social capital and networks as potential resources used by recent claimants in order to offset barriers related to their immigration status and escape the worst forms of homelessness.
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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 | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".