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Record W3134525617 · doi:10.1017/9781107300422

Justice in Extreme Cases

2020· book· en· W3134525617 on OpenAlexaff
Darryl Robinson

Bibliographic record

VenueCambridge University Press eBooks · 2020
Typebook
Languageen
FieldSocial Sciences
TopicInternational Law and Human Rights
Canadian institutionsQueen's University
Fundersnot available
KeywordsCoherentismCriminal lawMainstreamLawCriminal justiceTheory of criminal justiceEconomic JusticePolitical sciencePhilosophy of lawCriminal procedureCriminologySociologyEpistemologyPublic lawPhilosophy

Abstract

fetched live from OpenAlex

In Justice in Extreme Cases, Darryl Robinson argues that the encounter between criminal law theory and international criminal law (ICL) can be illuminating in two directions: criminal law theory can challenge and improve ICL, and conversely, ICL's novel puzzles can challenge and improve mainstream criminal law theory. Robinson recommends a 'coherentist' method for discussions of principles, justice and justification. Coherentism recognizes that prevailing understandings are fallible, contingent human constructs. This book will be a valuable resource to scholars and jurists in ICL, as well as scholars of criminal law theory and legal philosophy.

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 score0.858
Threshold uncertainty score0.849

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 studies0.0000.000
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 head0.120
GPT teacher head0.268
Teacher spread0.148 · 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

Citations16
Published2020
Admission routes1
Has abstractyes

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