“Mommy, can we speak English? Because it’s embarrassing to speak Farsi”: exploring identity construction in plurilingual Iranian-Canadian children
Bibliographic record
Abstract
In this study, I examine the plurilingual identity constructions and expressions of generation 1.5 Iranian-Canadian minors living in Canada, focusing on their perceptions across diverse sociocultural and educational spaces. Using a qualitative multiple-case study approach and drawing on positioning theory, I investigate the impact of social position on language learning and the dynamic interplay among heritage language maintenance, access to resources, and cultural capital. I employ a multi-method qualitative approach, including interviews with parents and children, children’s visual representations, and value-laden artifacts, to explore three main ideas: parents’ access to resources and capital, the role of heritage language and identity, and the role of children’s families and communities in supporting them in their language development. Findings reveal a close link between access to resources and plurilingual education, the existence of mono-lingual mindsets in some Canadian schools, and discriminatory practices that hinder children’s plurilingual identity construction. Children demonstrate resilience in the face of adversity, drawing upon their cultural capital and adapting to diverse social situations. Family language practices and emotional connections to relatives and the country of origin play crucial roles in supporting the development and maintenance of children’s heritage language and identity. This study contributes to a deeper understanding of the complex processes involved in constructing and expressing plurilingual identities while highlighting the need for a better understanding of social contexts and the implementation of appropriate language and socialization strategies to address the challenges.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.010 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".