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Reading Faust into International Criminal Law’s Metaphorical References to the Devil

2024· book-chapter· en· W4406694361 on OpenAlexaboutno aff
Edwin Bikundo

Bibliographic record

VenueEdinburgh University Press eBooks · 2024
Typebook-chapter
Languageen
FieldSocial Sciences
TopicLaw in Society and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsFAUSTReading (process)LawCriminal lawPolitical scienceLiteraturePhilosophyArt

Abstract

fetched live from OpenAlex

Metaphorical references to the devil in international criminal justice are various, varied and tap into a rich vein of allusion, association and meaning. These range from simple references to evil to more complex referencing to Faustian pacts of one form or the other, to the downright esoteric encompassing the arcane origins of the immunity erstwhile afforded to official acts. Kenyan President Uhuru Kenyatta’s statement ‘That devil shall be defeated’ as well as Canadian General Romeo Dallaire’s ‘Shake Hands with the Devil’ are two examples respectively resisting and promoting international individual criminal liability. That Carl Schmitt was asked by his interrogator at Nuremberg ‘when did you renounce the devil?’ and that defence counsel at the International Criminal court in the Kenyan Situation analogised the Kenyan government as being accused of entering into ‘a deal with the devil’, to the judge at Rudolf Kastner’s case in Israel related to Nazi-era crimes described him as having ‘sold his soul to the devil’; cut across perpetrators and victims and speak of knowing and willing compacts with evil in order to, allegedly, produce good. Which is to say that are all political theodicies explaining away evil by linking it in some causal way to good.

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 score0.807
Threshold uncertainty score0.899

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 science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.051
GPT teacher head0.280
Teacher spread0.229 · 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
Published2024
Admission routes1
Has abstractyes

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