The Talk of Tamils in Multilingual Montreal: A Study of Intersecting Language Ideologies in Nationalist Quebec
Bibliographic record
Abstract
Abstract In Montreal, racial, caste, socioeconomic, and gender inequalities are often masked as neutral‐seeming linguistic differences of dialect, register, and accent. These sociolinguistic hierarchies are upheld by intersecting language ideologies, or essentialised beliefs about language use and ethnic identity. Quebec nationalist and multicultural policies endorse language ideologies of linguistic purity and sociolinguistic compartmentalisation to depict a cohesive nation while maintaining its racial and ethnic distinctions. Similarly, Montreal Tamil diaspora leaders encourage different Tamil‐speaking groups to participate in sociolinguistically segregated domains to preserve purist linguistic standards and maintain socioeconomic, caste, and gender distinctions. Heritage language programmes reproduce these language‐based distinctions for differentiating between types of Québécois citizens, while Montreal Tamil youth selectively challenge or endorse such prescriptions to produce a range of social identities and linguistic practices that correspond to their experiences as ethnic and racial minorities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".