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Record W2336927949 · doi:10.1017/cbo9780511781261.002

Introduction

2010· book-chapter· en· W2336927949 on OpenAlexaff
Jutta Brunnée, Stephen J. Toope

Bibliographic record

VenueCambridge University Press eBooks · 2010
Typebook-chapter
Languageen
FieldSocial Sciences
TopicTerrorism, Counterterrorism, and Political Violence
Canadian institutionsUniversity of British ColumbiaUniversity of Toronto
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

On 15 February 2003, millions of people around the world marched in the streets of their towns and cities to protest the impending invasion of Iraq by a ‘coalition of the willing’ led by the government of the United States of America. Media reports conservatively estimated crowds of 750,000 in London, 600,000 in Madrid, 500,000 in Berlin, 150,000 in Melbourne, 100,000 in New York, and possibly over a million in Rome, where estimates varied wildly. Smaller, but vocal demonstrations were held in scores of cities around the world. When all the numbers are pulled together, this was probably one of the largest mass protests in human history. The motivations behind individual decisions to protest were undoubtedly various, but underlying many decisions was a sense that the planned invasion broke the rules of international law. In a contemporaneous address, Pope John Paul II invoked the Charter of the United Nations Organization ‘and international law itself’ to conclude that ‘war cannot be decided upon, even when it is a matter of ensuring the common good, except as the very last option and in accordance with very strict conditions, without ignoring the consequences for the civilian population both during and after the military operations’. A protester in Boston described the Iraq war as ‘unjust’ and ‘a war of aggression’. An 11-year-old Muslim boy protesting in Los Angeles declared: ‘We are here to show our support because we think [President George W.] Bush is doing something wrong … The U.N. inspectors, they didn’t get much time, and Bush is just bringing, like, flimsy 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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.664
Threshold uncertainty score0.947

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.3360.185

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 head0.020
GPT teacher head0.235
Teacher spread0.215 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

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

Citations2
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueCambridge University Press eBooksSame topicTerrorism, Counterterrorism, and Political ViolenceFrench-language works237,207