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The Unity of International Criminal Law

2020· book-chapter· en· W3034484900 on OpenAlexaff
Frédéric Megret

Bibliographic record

VenueOxford University Press eBooks · 2020
Typebook-chapter
Languageen
FieldSocial Sciences
TopicInternational Law and Human Rights
Canadian institutionsMcGill University
Fundersnot available
KeywordsCriminalizationCriminal lawPolitical scienceLawInternational lawLaw and economicsSociology

Abstract

fetched live from OpenAlex

Abstract This chapter suggests the need to rethink, on both doctrinal and political grounds, the distinction between core and transnational criminal law with a view to recovering a sense of the discipline of international criminal law’s lost unity. It identifies a tendency towards fragmentation and rarefication that has led both core crimes and the operation of international criminal tribunals to monopolize attention and increasingly be identified with ‘international criminal law’ (ICL). This chapter argues that, in addition to having a weak doctrinal basis, that distinction is theoretically and criminologically dubious. It suggests that the time may have come to recover at least a unified research agenda when it comes to ICL—one that rediscovers the extent to which supranational and transnational criminal law are at the very least joined at the hip. This involves better conceptualizing how the defining phenomenon of ICL is not only the criminalization of certain international law prohibitions, but also the ascendancy of certain ideas about crime control globally, as well as the degree to which both core crimes and transnational crimes rely on a common criminal corpus and conceptual baggage. The chapter ends with a call for renewed engagement with a sort of meta-theory of ICL, one that would make more sense of the relations between its diverse constituent parts.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.021
Scholarly communication0.0090.006
Open science0.0010.004
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0080.001

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 head0.248
Teacher spread0.209 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations3
Published2020
Admission routes1
Has abstractyes

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Same venueOxford University Press eBooksSame topicInternational Law and Human RightsFrench-language works237,207