Does anyone in the world care about Canadian language issues?
Bibliographic record
Abstract
n 2023, the Robarts Centre undertook a major study of the state of Canadian Studies and of Canadian Studies centres around the world.Researchers as well as executives of local associations of Canadian Studies abroad, including centres and networks, were invited to share their thoughts on the challenges of researching and teaching about Canada in their part of the world.One of the study's findings was that the country's linguistic question-the relationship between French and English, and the efforts and strategies to promote French as a common language in Québec and among francophone minority communities-left many people indifferent.Federal and official bilingualism as well as language planning policies were not a topic of study or a major theme in courses on Canada; neither were official languages and frameworks of provinces and territories.Should we conclude that students and researchers outside Canada are blasé about bilingualism in Canada's official languages?
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.032 | 0.008 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.014 | 0.016 |
| Insufficient payload (model declined to judge) | 0.032 | 0.003 |
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".