Bibliographic record
Abstract
This chapter looks at how Islamophobia is conceptualised and operates in Canada as a set of discourses and practices defined through the relationship between Muslims, racialisation, and coloniality. The racialised logics that underpin the construction of the Canadian national imaginary are grounded in the intersecting histories of English and French white settler-colonial projects. These racialised logics continue to shape the present-day relationship between white majorities and racialised Muslim minorities in Canada and Quebec, most visible in the 2017 Quebec City mosque shooting and its aftermath. This chapter situates this national analysis within the global and transnational elements that inform Islamophobia, such as the War on Terror and its securitisation of Muslims and the rise of xenophobic and Islamophobic far-right and white supremacist political groups in the United States, Canada and Quebec. The chapter concludes with a discussion of the emergence of Muslim political identity and agency as part of the active resistance to ongoing Islamophobic laws, political discourses, and actions.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.026 | 0.015 |
| Scholarly communication | 0.009 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".