The Terrorization of Muslim Canadians in a Post-9/11 Era: A Critical Analysis of Racial Profiling, Self-Identity and Surveillance
Bibliographic record
Abstract
Canada has been praised for its multicultural approach towards their policies and procedures regarding immigrants through its politized involvement with introducing multicultural literature in our constitution. However, the implementation of these policies and procedures questions the authenticity of these multicultural initiatives in relation to the overall security detainment, racial profiling and discrimination faced by Muslim Canadians in a post-9/11 era. The commoditization of immigrant practices prioritizing the coercive white social order needs to be addressed in relation to the inherent incline of religious and ethnical hierarchy that displaces those minority classifications. Specifically concerning the entrenched cleansing of Muslim bodies within a post-9/11 era, it is imperative to conceptualize the deliberate denigration and vilification of Muslim characteristics and practices as a means of augmenting existing surveillance practices. This paper explores into the terrorization of Canadian Muslim's race relations, identities and policing bodies in a post-9/11 era and their impacts on socio-economic relations of Canadian Muslims. Previous research has suggested that these security-based policies and procedures are the foundation of obscuring Muslim identities and furthermore forcing assimilation that highlights the preferential treatment of the white majority over the terrorist 'other'. Introducing the idea of reactive identity formation and identity concealment provides a robust approach in attempting to introduce literature and framework for combating racial profiling and the policing and surveillance of Muslim bodies through breaking down negative stereotypes manipulated into fear-mongering media and introducing the integration of Muslim literature in everyday practices. Keywords: Muslim identity, 9/11 effects, multiculturalism, racial profiling, terrorism
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.042 | 0.021 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| 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".