Appels alternés entre la liberté d’expression et la liberté de la religion : mise en relation de moments politiques au Canada contemporain
Bibliographic record
Abstract
This article analyses how arguments in Canadian newspaper op eds that promote the freedom of expression can serve as conduits for Islamophobia. To reflect on this slippage, we compare opinion pieces in five English-language daily newspapers on 2019’s Law 21 in Québec, and discussions surrounding Motion 103 in 2017, and the appointment of Amira Elghawaby as Canada’s Special Representative on Islamophobia in 2023. We show how ‘freedom of religion’ and ‘freedom of expression’ frameworks both construct a tolerant and modern Canadian nation in contrast to Québec. English-language media tend to promote Law 21 as discriminatory towards religious minorities, particularly Muslims, while their discussions of Motion 103 and the appointment of Amira Elghawaby nevertheless contain arguments with an Islamophobic slant. We conclude that anti-Islamophobia discourse in the Canadian English-language media thus remains fragile.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.024 | 0.020 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".