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The Global War

2020· book-chapter· en· W3165350203 on OpenAlexaboutno aff
Russell Crandall

Bibliographic record

VenueYale University Press eBooks · 2020
Typebook-chapter
Languageen
FieldSocial Sciences
TopicCrime, Illicit Activities, and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsLegislationPolitical scienceLicenseCITESParadeLaw enforcementScope (computer science)Latin AmericansMiddle EastTerrorismLawEnforcementPublic administration

Abstract

fetched live from OpenAlex

This chapter talks about how U.S. anti-drug enforcement achieved a fully global reach in the post-9/11 “Age of Terror.” It refers to opaque anti-drug missions that first piloted in Latin America and then exported to Thailand, Canada, Africa, Europe, and the Middle East, at times without the knowledge or cooperation of the governments concerned. It also provides an overview of a landmark piece of legislation passed by the Congress in 2006 that expanded the scope of American officials' presumptive license abroad, giving U.S. counter-narcotics agents legal standing to pursue narcotics and terrorism crimes committed anywhere in the world. The chapter cites the explosion of cocaine consumption in Europe over the first fifteen years of the twenty-first century as the key motivation for the new legislation in the global war on drugs. It mentions three Malian nationals who had been arrested in their home country by U.S. federal agents and extradited to the United States under the 2006 rule.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.966
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.032
GPT teacher head0.231
Teacher spread0.200 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2020
Admission routes1
Has abstractyes

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