INTERCULTURALISM, MULTICULTURALISM, AND THE STATE FUNDING AND REGULATION OF CONSERVATIVE RELIGIOUS SCHOOLS
Bibliographic record
Abstract
In this essay, Bruce Maxwell, David Waddington, Kevin McDonough, Andrée‐Anne Cormier, and Marina Schwimmer compare two competing approaches to social integration policy, Multiculturalism and Interculturalism, from the perspective of the issue of the state funding and regulation of conservative religious schools. After identifying the key differences between Interculturalism and Multiculturalism, as well as their many similarities, the authors present an explanatory analysis of this intractable policy challenge. Conservative religious schooling, they argue, tests a conceptual tension inherent in Multiculturalism between respect for group diversity and autonomy, on the one hand, and the ideal of intercultural citizenship, on the other. Taking as a case study Québec's education system and, in particular, recent curricular innovations aimed at helping young people acquire the capabilities of intercultural citizenship, the authors illustrate how Interculturalism signals a compelling way forward in the effort to overcome the political dilemma of conservative religious schooling.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.016 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".