Analysis of Settlement Experiences of Syrian Families in the Canadian Context
Bibliographic record
Abstract
This presentation will provide an overview of the movement of Syrian Refugees into Rural and Small-Town Ontario. It will identify specific challenges that refugees face and it will identify some of the positives and negatives associated with community sponsorship. The profile of Syrian refugees shows that they will face barriers to resettlement and integration in host communities. Literature suggests that refugees experience a difficult time entering the labor market upon arrival to Canada (Government of Canada, 2016; Lamba, 2003; Yu, Oulette & Warmington, 2007). In addition, most Syrian women also lack the proper education in their first language and also lack work experience. Changes in immigration policy have reduced government funds to settlement supports, and this negatively affects refugee settlement (Bauder & Shields, 2015). Objectives: What are the impacts of Syrian family size, age of children, and gender relations on the outcomes of Syrian refugee families. What are the key factors that determine the capacity of a community to attract and retain refugees, what service supports need to be in place for all members of refugee 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.017 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".