Lost in Translation? Bill 21, International Human Rights, and the Margin of Appreciation
Bibliographic record
Abstract
The adoption of Bill 21, which bans religious symbols for civil servants in Quebec, has stirred considerable debate politically and constitutionally in the province and in the rest of Canada. Neglected, however, has been a more in-depth analysis of how international human rights law often serves as an implicit frame of reference for many of the debates surrounding Bill 21. This essay focuses, in particular, on the invocation of the case law of the European Court of Human Rights, which seems to have validated bans of religious symbols in various contexts. It gives an overview of that jurisprudence and specifies the parameters within which it operates, emphasizing the complexity of translating a supranational case law into a domestic debate. It argues that whilst Quebec is less alone in banning religious symbols than is sometimes argued, the European case law needs to be handled carefully. In particular, the essay emphasizes the importance of the so-called “margin of appreciation” as heavily impacting the outcome in those cases. Although the margin suggests that there is national leeway in adopting bans based on certain national traditions and specificities, it hardly opens the door to all bans. Rather, the margin emphasizes the significance of divergences between states parties on an issue and respect for procedural safeguards. The essay concludes with some thoughts on how importing human rights arguments out of context can be perilous, but also about how the margin itself may be problematic.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.029 | 0.008 |
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".