Pervasive Anxiety about Islam: A Critical Reading of Contemporary ‘Clash’ Literature
Bibliographic record
Abstract
This article analyzes and critiques North American and European “clash literature”—a genre of post-9/11 writings that popularize elements of Samuel Huntington’s “clash of civilizations” thesis, with particular reference to putative threats posed to Western civilization by Islam and Muslims. Attention is given to a series of salient themes used by multiple texts and authors, in a manner that creates an overarching narrative of Western moral superiority vis-à-vis a monolithic, authoritarian, and misogynistic Islamic culture; betrayal of Western culture by “politically correct” intellectual elites wedded to ideas of multicultural accommodation; and a cascading threat posed by the rapid influx of unassimilable Muslim immigrants who are poised to mount a demographic takeover of Europe and possibly America as well. The content of clash texts is then analyzed and evaluated in light of its detachment from relevant scholarship, its reliance on highly essentialized identity constructs, its use of demographic extrapolations and alarming anecdotes, and its stark rejection of contemporary pluralism. The article concludes with reflections on how scholars might respond to the identity insecurities revealed by clash literature as they seek to advance alternative narratives based on values of dialogue and coexistence.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.018 | 0.048 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.002 | 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".