Why Are You âActiveâ? -Voices of Young Muslim Women Post-9/11
Bibliographic record
Abstract
Contributing to the literature on the Muslim experience post-9/11, the purpose of this study was to engage with a group that is often talked about, but not with: Muslim youth. Using an integrative anti-racist and anti-colonial approach with an emphasis on a spiritual way of knowing, this study gives voice to young Muslim activists in Toronto who have made the choice to âdo somethingâ. The study aims to understand what motivates these young activists, particularly in the context of post-9/11 Islamophobia, with the goal being to challenge stereotypical perceptions of Muslims, while contributing to the body of knowledge that aims to disrupt dominant notions of what âCanadianâ identity is. The following analysis helps answer this question, which includes the role of spirituality, the attachment to Canadian identity and the desire to educate. Key challenges and what these youth prescribe for Canadaâs future are also discussed.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".