Exploring occupational transitions of Syrian refugee youth to Canada
Bibliographic record
Abstract
Introduction Since 2015, nearly 45,000 Syrian refugees who fled the civil war have resettled in Canada. This forced migration can present significant disruptions for Syrian refugees’ everyday lives. Refugee youth may experience distinct changes in their occupations and roles, such as schooling and caring for family. Research exploring Syrian refugee youth’s experiences of occupational transition to Canada is largely absent.Objectives This study explores the experiences of occupational transition of Syrian refugee youth along their migration journey to Canada.Method Using narrative inquiry, two individual semi-structured interviews incorporating a co-created occupational life course timeline were conducted via videoconferencing with two 19-year-old and two 20-year-old Syrian refugee youth. Generated narratives were thematically analyzed to explore their experiences of occupational transition and how participants’ occupations evolved through the migration journey.Findings The findings revealed an overarching grand narrative of “occupational possibilities unfolding through the migration journey.” Within this grand narrative, four themes were generated: finding a place in society, contributing to the family, experiencing structured autonomy, and giving back to the community. These findings illustrate how occupations and roles are shaped by sociocultural contexts across the migration journey.Conclusion The Syrian refugee youth who participated in this study illustrated through their narratives how their personal occupational experiences were shaped by cultural and sociopolitical contexts of the countries in which they lived along their migration journey to Canada. These contexts shaped their self-development, advocacy, and roles due to variability in access to occupations and their level of engagement.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.007 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".