Defining Terrorism: A Comparison of Several Judicial-Executive Dialogues
Bibliographic record
Abstract
The events of 9/11 have forced upon the entire community of Western states a re-assessment of their respective anti-terrorism policies and laws. It released an intense discussion seeking to update and re-characterize the post-9/11 state of international relations producing a wave of renewed attempts to legally (re)define terrorism. The main challenge is to determine whether terrorism in its twenty-first century manifestation warrants recognition as a component within the doctrine of armed conflict and what would be the effects of such transformation. This article compares how the judiciary in Western liberal and pluralist democracies has been tackling this dilemma and affecting respective legislative responses. The article offers preliminary thoughts as guidelines to the design of parameters for an approach to anti-terrorism security that is common to North America (and the rest of the world). To this effect, it contextualizes the relevant North American jurisprudential developments within a sample of other Western-oriented judicial track records. The article finds that the North American dialogue (in Canada and the US) among the three branches of government is departing from two opposite ends of one and the same Western War on Terror adjudicative spectrum. This context appears to be slowly, but eventually, progressing toward conversion, effecting a common re-characterization and definition of terrorism, anti-terrorism, and their place within the doctrine of armed conflict.
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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 | 0.010 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.015 | 0.015 |
| Scholarly communication | 0.014 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| 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".