Bibliographic record
Abstract
The powerful story of how the War on Terror created the conditions for the emergence of a novel theory of jihad The post-9/11 period saw the emergence of the figure of the homegrown radical Muslim, raising fears and worries about the possibility of an enemy exceptionally capable of harming and destabilizing the nation-state. Against this figure of the radical stood that of the moderate Muslim who represented the possibility of national unity despite religious and racial differences. In Homegrown Radicals , Youcef Soufi brings the radical and moderate Muslim together in uneasy tension, offering a study into how state violence inextricably tied them together in post-9/11 Canada and the US. By focusing on the radicalization of three Muslim students on the Canadian prairies, it traces North American Muslims’ general sense of affective injury over the loss of Muslim life in Western military campaigns overseas. In this context, a new theory of jihad rooted in a Muslim utopian imagination emerged, one that marked a significant rupture with premodern Islamic thought. The three “radicals” focused upon in this book were among thousands of Anglophone Muslims who found this new theory compelling as a diagnosis and solution to the violence unleashed in the War on Terror. The book examines how, why, and with what consequences for their families, friends, and Muslim community. In so doing it highlights that post 9/11 Islamophobia has operated through the conceptual blurring of the line between the “moderate” and “radical” Muslims and asks what alternative forms of solidarity may transcend the violent boundaries of the nation-state.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.013 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.033 | 0.004 |
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".