Re/claiming our identities : thinking through Islamophobia, the veil, and "the Muslim woman" in Canadian cultural productions
Bibliographic record
Abstract
Western, Islamophobic, and Islamic discourses have resulted in a contested terrain of representations through which the lives of Muslims have been debated and consumed. Post 9/11, Muslims assumed a hyper visibility evident in their being stigmatized in the West as terrorists, and as threats to national security, democratic values, and time-honoured cultural practices in Western societies. As such, the presence of Muslim communities in Western nations is raising questions about national identity and belonging, particularly in the Canadian context. An important concern is to identify and interrogate the points of conflict and tension between Muslims and non-Muslim Canadians, particularly in regard to issues of national identity and citizenship. By focusing specifically on recent cultural productions, including a film, a television sitcom, and a novel by female Muslim Canadians, the analysis will demonstrate the extent to which the voices of Muslim women intervene into dominant Western discourses about Islam and popular representations of Muslims in the West. Special attention will be given to the symbolism of the veil to show how it has become the central marker of "difference" and one of the main "problems" affecting Western perception of Muslim immigrants and these communities' integration and assimilation into Canadian and Western societies.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.039 | 0.029 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".