Welcoming Communities? An Assessment of Community Services in Attracting and Retaining Immigrants in the South Okanagan Valley (British Columbia, Canada), with Policy Recommendations
Bibliographic record
Abstract
The urban bias of Canadian immigration has led to policies intended to redirect immigration away from major metropolitan areas. Policy makers have identified the Okanagan Valley in British Columbia as a region that could benefit from additional immigration. Whether the policy succeeds depends on the presence of (a) quality services in a welcoming community; (b) affordable, suitable, and adequate housing; (c) educational opportunities; (d) employment opportunities that offer an adequate income; and (e) opportunities to integrate into the community. This study evaluates community services and their role in attracting and retaining immigrants to the South Okanagan, a sub-region of the Okanagan Valley. The study uses data from four focus groups with 31 immigrants, 10 semi-structured interviews with immigrants, and 15 interviews with key informants. The researchers found that immigrants face two major obstacles in their service use: physical access, given the near-absence of an effective public transportation system; and financial instability, as many of the surveyed immigrants rely on low-paying 'survival jobs' in the cyclical tourism and service industry. These findings have led to recommendations to improve regional socio-economic conditions. Keywords: Regionalization of immigration, community services, immigration, economic development, Okanagan Valley, Canada
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".