Has the Third World War Broken Out? Reflections on the Place of Terrorism in International Conflict and its Impact on the Transformation of the Law of War
Bibliographic record
Abstract
country wasn't on a war footing and yet we were at (President Bush at a national televised news conference, April 13, 2004)From the standpoint of scientific cognition positive law, its justification by a moral order different from the legal order, is irrelevant, because the task of the science of law is not to approve or disapprove its subjects, but to know and describe it. True legal norms as prescription of what ought to be, constitute values; yet the function of the science of law is not the evaluation of its subject but its value-free description. The legal scientist does not identify with any value, not even the legal value he describes. (Keslen qtd. in Harris 116).The new war - the War on Terrorism - declared by President Bush in the wake of the September 11, 2001 terrorist attack in the united States has propelled a heated debate engulfing the mass media, academe, political fora, civil society, and the military, to name a few. The issues discussed have ranged from privacy rights to collective security, contest of civilisations, post 9/11 world order, etc. In this paper, I am focusing on one dilemma out of the wide spectrum of the post 9/11 generated enigma, namely the nature of international war. I am trying to think beyond fixed formats and offer a particular angle through which to engage in a debate about the nature of contemporary international war.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.028 | 0.054 |
| Scholarly communication | 0.021 | 0.017 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.011 | 0.017 |
| Insufficient payload (model declined to judge) | 0.007 | 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".