African Refugee Youth’s Experiences of Navigating Different Cultures in Canada: A “Push and Pull” Experience
Bibliographic record
Abstract
Refugee youth face challenges in navigating different cultures in destination countries and require better support. However, we know little about the adaptation experiences of African refugee youth in Canada. Accordingly, this paper presents the adaptation experiences of African refugee youth and makes recommendations for ways to support youth. Twenty-eight youth took part in semi-structured interviews. Using a thematic analysis approach, qualitative data revealed four themes of: (1) ‘disruption in the family,’ where youth talked about being separated from their parent(s) and the effect on their adaptation; (2) ‘our cultures are different,’ where youth shared differences between African and mainstream Canadian culture; (3) ‘searching for identity: a cultural struggle,’ where youth narrated their struggles in finding identity; and (4) ‘learning the new culture,’ where youth narrated how they navigate African and Canadian culture. Overall, the youth presented with challenges in adapting to cultures in Canada and highlighted how these struggles were influenced by their migration journey. To promote better settlement and adaptation, youth could benefit from supports and activities that promote cultural awareness with attention to their migration experiences. Service providers could benefit from newcomer-friendly and culturally sensitive training on salient ways of how experiences of multiple cultures affect integration outcomes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.036 | 0.009 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.004 |
| 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".