Forging a new home: community size shapes the settlement experience of Syrian refugees in Canada
Bibliographic record
Abstract
Many immigration and settlement studies in Canada focus on large urban centers, leaving a gap in research addressing the unique needs and experiences of newcomers in smaller communities. This phenomenological research delves into the settlement experiences of Syrian refugees in the small city of St. John’s, compared to those in the larger city of Ottawa. Through one-on-one, in-person, semi-structured interviews with seven Syrian refugees in St. John’s and eight in Ottawa, data was collected, and thematic analysis was used to gain insights into the data. The study reveals that St. John’s provided a haven for Syrian refugees escaping war. However, its lower ethnic, cultural, and linguistic diversity compared to larger cities challenged Syrian refugees’ integration. Additionally, their economic integration was hindered by inadequate settlement services, difficulties with the recognition of foreign acquired skills and experience, workplace discrimination, and language barriers. In contrast, interviewees from Ottawa reported being well-integrated into the social and economic fabric of the city without perceiving the same barriers perceived by the Syrian refugees in St. John’s. These findings stress the need for new settlement programs and services. They also highlight the significance of fostering the economic integration of refugees by providing them with the support they need.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".