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Record W2612826296 · doi:10.6000/1929-4409.2017.06.06

The Evolution of International Criminal Tribunals

2017· article· en· W2612826296 on OpenAlexvenueno aff
Harry M. Rhea

Bibliographic record

VenueInternational Journal of Criminology and Sociology · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Law and Human Rights
Canadian institutionsnot available
Fundersnot available
KeywordsCrimes against humanityTribunalGenocideLawWar crimeCriminal lawPolitical scienceInternational lawCriminal justiceTheory of criminal justiceCriminal procedureCriminologySociology

Abstract

fetched live from OpenAlex

International criminal justice is a relatively new and uniquely distinct system of criminal justice. It combines international law and criminal law from various legal systems. Historically, international law applied only to States; however, it is now applied to individuals through its merging with criminal law. The majority of States have been genuinely unwilling or unable to prosecute those most responsible for the planning and commission of international crimes. This lack of genuine willingness to prosecute perpetrators of genocide, war crimes, and crimes against humanity has resulted in the recent creation of multiple international criminal tribunals. The emergence of international and quasi-international criminal tribunals should not reflect the assumption that the idea of such courts is new. On the contrary, the idea and discussions for creating international criminal tribunals have been with us for well over a century. This article traces the evolution of international criminal tribunals starting from 1864. Each major debate to establish an international criminal tribunal is closely analyzed. The article concludes with analysis of the International Criminal Court.

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)0.005
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.015
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0050.004
Science and technology studies0.0120.016
Scholarly communication0.0150.007
Open science0.0020.006
Research integrity0.0020.007
Insufficient payload (model declined to judge)0.0090.001

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 head0.069
GPT teacher head0.386
Teacher spread0.317 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations1
Published2017
Admission routes1
Has abstractyes

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