Religiosity matters: assessing competing explanations of support for secularism in Quebec and Canada
Bibliographic record
Abstract
Abstract Secularism—i.e., the separation between the state and religious institutions—is a fundamental characteristic of liberal democracies, yet support for secular arrangements varies significantly across Western countries. In Canada, such attitudinal divergences are observable at the regional level, with citizens from Quebec displaying higher levels of support for secularism than other Canadians. In this paper, we test three hypotheses to account for this regional discrepancy: religiosity, liberal values, and out-group prejudice. Using data from an online panel survey ( n = 2,000), our findings suggest that support for secularism in Quebec is mostly explained by the province's lower baseline levels of religiosity, anticlerical feelings, and by its distinctive understanding of liberalism. These factors are likely to result from Quebec's unique religious and sociohistorical history. Results also suggest that while negative feelings toward religious minorities are positively correlated with support for secularism across the entire country, negative feelings toward ethnic minorities are associated with lower support for secularism in Quebec. These findings disprove the commonly held assumption according to which support for secularism is driven by ethnic prejudice in Quebec.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".