Bibliographic record
Abstract
Compared to other Western democracies, there has been relatively stable support for multiculturalism in Canada since its adoption in 1971, both amongst the general public and amongst the three main political parties. Conservative opposition to multiculturalism has, therefore, typically taken the form of “stealth” reforms to undercut its progressive potential, not direct frontal attacks. During the 2015 election, however, the Conservative Party campaigned on an explicitly anti-multiculturalist platform. This provided a clear opportunity to test “Canadian exceptionalism” in relation to public support for multiculturalism. In this article, I explore the Conservatives’ strategy, and its impact on the election. The evidence suggests that a significant part of the Canadian electorate was responsive to an anti-multicultural—and more specifically anti-Muslim—discourse. However, when this discourse was pushed too far, voters recoiled from what was perceived as an excessive, and indeed “unCanadian,” politics of distrust and division. The article explores different ways of understanding this tipping point, and what it tells us about the precarious resilience of multiculturalism in Canada.
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.012 |
| Science and technology studies | 0.013 | 0.011 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".