Identity texts: an intervention to internationalise the classroom
Bibliographic record
Abstract
The growing number of international students studying at Canadian universities has exacerbated the need to address identity, cultural aspects of teaching, and the commonalities of different cultures through a transcultural lens. To explore these concepts, researchers conducted a qualitative study using a workshop format at a large university in western Canada with graduate students, postdoctoral students, and faculty members from multiethnic backgrounds (N = 9). Two questions were posed to precipitate the research: 1) What does being transcultural mean to you? 2) Have you experienced cultural dissonance as part of your professional life? In a series of three activities, participants explored how to use identity texts (written, spoken, visual, musical, or multimodal sociocultural artefacts produced by participants) as an intervention to foster transculturalism and reduce tension and dissonance in a cross-cultural educational setting. Results indicated that using identity texts increased self-awareness, built trust, enhanced belonging, and revealed common humanity, thus creating opportunities to develop a successful professional identity in a multiethnic milieu.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".