Negotiating Pluralism in Québec: Identity, Religion, and Secularism in the Debate over “Reasonable Accommodation”
Bibliographic record
Abstract
Abstract Once nicknamed “the priest-ridden province,” Québec is now a strikingly secular place. During the so-called Quiet Revolution of the 1960s, the Québécois dramatically rid themselves of Catholicism, amputating what a new generation of social activists and political figures came to see as a gangrenous limb preventing the healthy development of the nation. Yet religion, it turns out, is present not only in the lives of “others” but also as a skeleton in Québec's closet that is often experienced as phantom limb pain. This became apparent in the debates over the religious practices of cultural minorities, which were at the center of public life from 2006 to 2008. Analysis of the debates reveals that what was at stake was as much about Québec's religious past as it was about its present religious landscape and the challenges it poses for a self-avowed secular society. The Québécois case is also helpful to think about the meaning and stakes of religious pluralism and secularism in contexts very different from that of the United States or France, which offer the prevailing models. Through an analysis of the debates over reasonable accommodation, this chapter shows that Québec is currently trying to find its own way between the French, American, and Canadian models of laïcité, pluralism, and multiculturalism.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.024 | 0.023 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".