Arts-based methodologies to explore Asian-Canadian youth identities in the Greater Toronto Area: Sharing some implementation experiences from the field
Bibliographic record
Abstract
Cultural identity is a complex, fluid and context bound concept. Cultural identity is informed by immigrant and second-generation youths’ experiences of adaptation and integration. Cultural identity has also been linked to youth mental health and wellbeing. Research recognizes the need to develop research tools to better capture and understand youths’ lived experiences with their identity and integration in multicultural settings. We present preliminary research findings from our community-based project that applied arts-based methodologies to explore Asian-Canadian youth identities in the Greater Toronto Area in Canada. Inclusion criteria were (i) youth between the ages of 16-29 and (ii) who self-identify as Asian or Asian-Canadian. We organized two workshops with youth participants. In workshop 1 we applied visual arts: Self-Portrait and a Relational Map. In workshop 2 we applied drama (Readers’ Theatre). Youth feedback highlighted the effectiveness of arts-based methodologies in (i) helping youth to discuss their lived experiences without feeling like they were under evaluation, (ii) providing a universal way of communicating their experiences and, (iii) allowing youth to think of issues that participants had not previously reflected on. We also shared some implementation experiences. This pilot study informed implementation strategies for a current larger project that has the objective of evaluating the effectiveness of arts-based methodologies to explore Asian-Canadian youth identities.
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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 | 0.020 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.030 | 0.015 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".