Building a life : integration outcomes among government-assisted refugee newcomers in Greater Vancouver
Bibliographic record
Abstract
This thesis focuses on integration outcomes among government-assisted refugees (GARs) who arrived in Canada between 2007-2016. I explore how this cohort is faring relative to basic indicators like employment, health, and social connections, and I examine how GARs themselves understand integration as a concept. I explain my mixed-methods approach to answering these questions, and I present the results of fieldwork undertaken in Greater Vancouver, British Columbia in early-mid 2019. I also provide a short review of the literature of integration, and I wrestle with ethical and methodological issues raised by the process of researching a vulnerable group. I conclude that legislation changes at the federal level have impacted the demographic characteristics of refugees selected for resettlement, with newcomers facing substantial barriers with respect to labour market integration, access to stable housing, and overcoming trauma. I also conclude that refugees’ own understandings of integration do not differ substantially from the framework proposed by Ager and Strang (2008). Finally, I offer recommendations for future research into migration and changes to family dynamics, the impact of degree recognition programs, and facilitating the social integration of LGBT+ refugees.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| 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".