Multiple Minorities or Culturally and Linguistically Diverse (CLD) Plurilingual Learners? Re-envisioning Allophone Immigrant Children and Their Inclusion in French-Language Schools in Ontario
Bibliographic record
Abstract
Abstract: Four out of five immigrants to Canada speak a language other than English or French as a first language. Immigration is increasingly transforming francophone minority communities. Allophone children acquire minority status on multiple levels within French-language schools, where they can become both a linguistic minority and a cultural minority within an official francophone minority in Canada. This article examines how culturally and linguistically diverse (CLD) allophones have been constructed historically through official language and multiculturalism policies in Canada and how this political framing limits language rights and schooling for allophone immigrant children. By examining recent language policies, this article argues that the ways in which policy makers, educators, and researchers conceptualize CLD children shape their integration into Canada. This article draws upon a case study of teachers’ practices with allophone learners in one French-language school to highlight the potential for transformative third-space practices to support CLD children in French-language schools.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.016 | 0.008 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| 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".