Arts-based engagement ethnography with newcomer youth in Canada: Learning from their experiences.
Bibliographic record
Abstract
Newcomer youth experience unique challenges when integrating into high schools in their host countries. As newcomer communities grow across Canada, high schools are faced with the increased challenge of meeting their needs. Schools are often the first point of contact for newcomer youth, and their experiences of school integration can directly impact other aspects of their integration experience, including mental and physical health, relationships with friends and family, and the ability to fit into broader society. This research started with the question: How do newcomer youth experience school integration following migration to Canada? Using an art-based engagement ethnography (ABEE), coupled with a social justice framework, our aim was to capture newcomer youth’s experiences of school integration in order to identify ways in which schools, teachers, and practitioners, as well as the broader education system, could better support these students. Using cultural probes (e.g., maps, journals, cameras), qualitative interviews, and focus groups, four participants documented their everyday experiences of school integration. An ethnographic analysis of these materials revealed three interconnected structures (challenges to school integration; responses and resiliencies in the face of challenges, and; understanding of identity during school integration) as well as specific recommendations from participants for improving the experiences of other newcomer students. These are conveyed in two manuscripts that together give both a nuanced look into the experiences of newcomer students and suggestions for practitioners and policy makers who wish to support these youth.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.025 | 0.010 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 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".