The Myth of Religious Violence: Secular Ideology and the Roots of Modern Conflict
Bibliographic record
Abstract
As the world approaches the tenth anniversary of 9/11 (September 11, 2001), there is a need for pause about the kind and quality of scholarship that has emerged from not simply the events of that day but also the subsequent and so-called Global War on Terror. Much of the scholarship over the last decade has been timely. Much more of it has been alarmist. Written in the style of an intervention, with a robust appreciation for the power of myth on human action and comprehension, William Cavanaugh's The Myth of Religious Violence represents a long awaited voice of reason. Cavanaugh's book centers on the tendency for scholars to understand religion as violent—as promoting violence, as having the means to incite violence, as being comprised of violent characters. This myth of religious violence, as Cavanaugh puts its, underlies many of the institutions and policies that promote liberal democracy in and beyond the Middle East as well as much of the scholarship produced today. Entangled in this myth is also the recurring promise of secularism—a more advanced, even peaceful, way of being. This myth, Cavanaugh argues, is not just false but also obstructs the West's moral vision.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.015 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".