‘My multiple cultural backgrounds are pulling me in all directions with my identity’: Asian and Latino Canadian youth experiences of cultural identity
Bibliographic record
Abstract
Identity, diversity, and inclusion are constantly being reshaped in the face of global migration and resettlement. New research is needed that examines youth identities. In this article, we analyse Asian and Latino youth’s understandings and experiences of how their cultural identity has been influenced by exclusion, inequitable access and racism on the part of their host society. We report on a qualitative study; focus groups (2) and individual interviews were conducted with 15 youth participants. Analysis process included code-driven guided by grounded theory. Youth narratives resisted oversimplified representations by inserting their gendered, minority, and youth identity within mainstream multicultural narratives to make visible immigrant youth experiences. Interwoven in youth’s narratives were experiences of racial discrimination, gender inequality, and indeterminate belonging. Cultural identity is a complex and changing concept. We analyse how youth living in multicultural view their need to negotiate their identities to adapt to their challenging multicultural context where they live.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.030 | 0.011 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| 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".