Fragile Trust: Muslim Communities in Canada and the R v. NS Decision
Bibliographic record
Abstract
Abstract In December 2012, the Canadian Supreme Court issued a ruling in R v. NS, in which a Muslim woman had demanded – citing her right to freedom of religion, as protected in the Canadian Charter of Rights and Freedoms – the right to cover her face, while giving testimony in a court of law. The defendants, also Muslim, demanded the right to see her face, in particular during cross-examination, as part of their right to the demeanor evidence that is necessary to provide “full answer and defense” and more generally as part of their right to a fair trial. The Supreme Court’s ruling stated that trial judges are entitled to make determinations about whether facial coverings must be removed, by weighing the rights of the accused to a fair trial against the rights of the accuser to freedom of religious practice, via what the court termed a “sincerity test.” This article considers the impact of the ruling and ultimately suggests that the decision will harm trust relations in Canada. In particular, the justifications offered in the judgment fail to respect the central objective of Canadian multiculturalism, i. e., to build trust among citizens of diverse backgrounds as a foundation for integrating minority communities into the public sphere on fair terms.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.039 | 0.012 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.010 | 0.011 |
| Insufficient payload (model declined to judge) | 0.007 | 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".