Friends, Neighbours, Townspeople and Parties: Explaining Canadian Attitudes toward Muslims
Bibliographic record
Abstract
Abstract The 2015 Canadian federal election campaign put into focus relations between Muslim communities in Canada and wider Canadian society, featuring debates around banning the niqab, and a “barbaric cultural practices” hotline. At the same time, challenges in relations between Muslims and majority-group Canadians were not a new development in 2015: they had in the past faced periodic strains due to terrorism-related events, and attacks targeting Muslims in Canada. The Canadian case is in fact reflective of a challenge in intergroup relations facing several Western democracies. In light of this, what accounts for majority-group Canadians’ attitudes toward Muslims in Canada? Drawing on data from the 2011 and 2015 Canadian Election Studies and theories linking outgroup perceptions to intergroup contact (friends), local demographic context at both the micro-level (neighbours) and meso-level (townspeople), and political factors (parties), this article seeks to explain why majority-group Canadians hold alternately positive or negative views of Muslims.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; both teacher heads agree on what is shown here.
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".