Were Muslim Barbarians Really Knocking on the Gates of Ontario?: The Religious Arbitration Controversy - Another Perspective
Bibliographic record
Abstract
The religious arbitration controversy created a moral panic that Muslim barbarians were knocking on the gates of Ontario. Historically, feminists have rightly criticized patriarchal approaches to religious practice that have limited/excluded women's participation in matters of everyday and/or religious life. In the recent sharia debate, feminist organizations were critical in exposing several deficiencies in the Arbitration Act that had an unduly burdensome impact on women. Relying on their analysis, feminists successfully lobbied to proscribe religious arbitration as the only acceptable means of protecting vulnerable women. It was resolved that the interests of women, Muslim women in particular, were best protected through the strict separation of law and religion. However, this strategy of secularism as the obvious solution to gender inequality was problematic for a number of reasons. First, it showed no consideration for religious women who might want to live a faith-based life. Second, feminist endorsement of an exclusively state run apparatus failed to understand legitimate resistance to government policies post 9/11 that have perpetuated punitive and stigmatizing measures against people of colour. Finally, the supposed ban on religious arbitration failed to prohibit religious arbitration at all; it merely perpetuated the Orientalist dichotomy between the enlightened West and backward Islam.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.026 | 0.016 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".