The challenges of linguistic duality for francophone Canada: contact, conflict and continuity
Bibliographic record
Abstract
This article analyses the principle and practice of linguistic duality in Canada, a country where official bilingualism has been rooted in federal policy on language issues since Confederation (1867). A recent example of a major federal initiative is theAction Plan for Official Languages(2003), which has set as one of its objectives the doubling of bilingual high-school graduates. Historically, conflict has characterized the relationship between the federal government and the provincial government of Quebec, which has pursued a diametrically opposed policy of official monolingualism, culminating in the enactment of theCharte de la langue franaise(Bill 101) in 1977. Several of the provisions of Bill 101 have been challenged in the Supreme Court, in the context of the Canadian Charter of Rights and Freedoms (1982), notably in the area of minority education rights (e.g. Casimir case, 2005). Analysis of the 2001 census data is used to discuss the demolinguistic reality of French, leading to the conclusion that it is under threat in all provinces and territories except Quebec. The issues of language contact are also challenging for Quebec; though it is the only province with a francophone majority, it is also the province with the highest rate of bilingualism. Important research projects on the long-term continuity and vitality of francophone minority communities are ongoing.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.066 | 0.033 |
| Scholarly communication | 0.019 | 0.006 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".