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Record W4366809599 · doi:10.1353/rss.2014.0015

Preventing the Crime of Silence

2014· article· en· W4366809599 on OpenAlexvenueno aff
Stefan Andersson

Bibliographic record

VenueRussell the Journal of Bertrand Russell Studies · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicMilitary History and Strategy
Canadian institutionsnot available
Fundersnot available
KeywordsSilenceTribunalCommitSpanish Civil WarWar crimeLawCommissionVietnam WarHistoryPolitical scienceArtComputer science

Abstract

fetched live from OpenAlex

94 Reviews c:\users\kenneth\documents\type3401\rj 3401 193 red.docx 2014-05-14 8:54 PM PREVENTING THE CRIME OF SILENCE Stefan Andersson stefankarlandersson@live.com Nick Turse. Kill Anything That Moves: the Real American War in Vietnam. New York: Henry Holt, 2013. Pp. xii, 372. us$30(hb), $17 (pb). isbn: 0805086919. urse’s well documented book has received praise from most reviewers, including the late Jonathan Schell and Chris Hedges, for its exposure of American war crimes during the Vietnam War. Michael Uhl (http://www. inthemindfield.com/2013/04/05/) is not equally impressed by the claim of novelty . He played an important role in organizing and participating in former GIs publicly testifying about war crimes. The first time this happened was at the second session of the Russell’s International War Crimes Tribunal held near Copenhagen in fall 1967. Turse refers to it, but only once (Ch. 7, n.50) to the work done by the cci (Citizens’ Commission of Inquiry into us War Crimes in Indochina), founded by Ralph Schoenman in November 1969 in New York, upon news of the My Lai massacre. Early in 1970 Tod Ensign and Jeremy Rifkin took over, followed by Uhl. Through their work and the vvaw (Vietnam Veterans Against the War), the torch from the Tribunal was carried to GIs in the us, who were determined not to commit the crime of silence. q= ...

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)0.006
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.583
Threshold uncertainty score0.911

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
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 head0.039
GPT teacher head0.312
Teacher spread0.274 · 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 designQualitative
Domainnot available
GenreEmpirical

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
Published2014
Admission routes1
Has abstractyes

Explore more

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