Bill C-13 and the Constitutionally Conflicting Bilingualism in Canada: An Analysis of Three Provincial Approaches to Separate French Education Following the Implementation of the Official Languages Act and Its Larger Impact
Bibliographic record
Abstract
The Official Languages Act (OLA) was enacted in 1969, making French and English the official languages of Canada. On May 13, 2023, the federal government amended the OLA for the first time since its creation in 1969 through Bill C-13. While scholars focus on what has been noted as the “big issue” with Bill C-13 – the possible excessive use of the “notwithstanding clause” – I argue that the impact of provincial legislation produced in response to Bill C-13 has been overlooked. By examining the historical rise of official language rights in Canada and the position of French-speaking minorities in Ontario, New Brunswick, and Alberta and their fight for separate French education, I shed light on the history of bilingualism and the competing federal-provincial laws following its application in 1969. I assert that despite various efforts by the federal government to implement language laws to protect francophone minorities and encourage bilingualism as a national narrative, calculated actions at provincial levels reflect the dominant Anglo-Saxon narrative rooted deep within the nation. The lack of unity between federal and provincial governments results in indirect, competing definitions of Canadian national identity and continued questioning of the place of bilingualism in Canada.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.044 | 0.022 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".