Bibliographic record
Abstract
North American law has been transformed in ways unimaginable before 9/11. Laws now authorize and courts have condoned indefinite detention without charge on secret evidence, mass secret surveillance, and targeted killing of U.S. citizens, suggesting a shift in the cultural currency of a liberal form of legality to authoritarian legality. This book demonstrates that extreme measures have been consistently embraced in politics, scholarship, and public opinion not in terms of a general fear of the greater threat that terrorism now poses, but in a more specific belief that 9/11 was the harbinger of a new order of terror giving rise to the likelihood in the near future of an attack on the same scale as 9/11 or greater, involving thousands or more casualties and possibly weapons of mass destruction (WMDs). The book surveys U.S. and Canadian counterterrorism law and policy marking the shift to authoritarian legality, and traces the role of the harbinger theory across a range of discourses — political, popular, and scholarly — to demonstrate the consistency and pervasiveness of the harbinger theory in support of extreme measures. The book also offers a unique overview of a range of skeptical evidence about the likelihood of mass terror involving nuclear, biological, and radiological weapons, as well as conventional means, arguing that a potentially more effective basis for reform advocacy is not to dismiss overstated claims of threats as implausible or psychologically grounded, but to challenge them directly through the use of contrary evidence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.494 | 0.314 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".