Race and language learning in multicultural Canada: towards critical antiracism
Bibliographic record
Abstract
Issues of race constitute an emerging area of inquiry in language education. Yet, race, racialisation and racism are still stigmatised topics of discussion in everyday and professional contexts in multiracial and multiethnic countries. Canada is especially an interesting context in this regard due to its official policy of multiculturalism that constructs a national identity of tolerance towards diversity. Drawing on the author's personal experience, this article presents some fundamental ideas for critical antiracism which call into question the commonly accepted antiracist agenda in research and practice. These ideas include decolonising antiracism (moving beyond white vs. non-white dichotomy to scrutinise power relations between non-white settlers and aboriginal people), de-essentialising antiracism (paying increased attention to economic privilege) and de-simplifying and de-silencing antiracism (paying more attention to multifaceted forms of racism and making issues of racial inequalities explicit). Such critical reflectivity enables us to understand racism in broader relations of power and to take greater ethical responsibility in antiracism.
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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 | 0.021 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.061 | 0.072 |
| Scholarly communication | 0.020 | 0.008 |
| Open science | 0.004 | 0.018 |
| Research integrity | 0.004 | 0.012 |
| 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".