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Record W7040051586

Introduction

2015· article· en· W7040051586 on OpenAlexaboutno aff

Bibliographic record

VenueArca (British Columbia Electronic Library Network) · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicTorture, Ethics, and Law
Canadian institutionsnot available
Fundersnot available
KeywordsPretextCircumstantial evidenceSubpoenaLimitingArticular cartilage damageNucleofection
DOInot available

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.872
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0620.000

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.

Opus teacher head0.015
GPT teacher head0.234
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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