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Record W2227678607

Searching for Law While Seeking Justice: The Difficulties of Enforcing International Humanitarian Law in International Criminal Trials

2008· article· en· W2227678607 on OpenAlexaff
Benjamin Perrin

Bibliographic record

VenueeYLS (Yale Law School) · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Law and Human Rights
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsLawPolitical sciencePublic lawCriminal lawInternational lawInternational humanitarian lawPublic international lawComparative lawStatuteTribunalMunicipal lawCriminal procedureHuman rightsCriminal justice
DOInot available

Abstract

fetched live from OpenAlex

International criminal law finds itself at the confluence of public international law, international humanitarian law, human rights law and national criminal laws. Our understanding of the interrelationship between these sources of law has been hampered by the conventional wisdom that public international law doctrines applicable to disputes between states can be readily transposed to the international criminal prosecution of individuals. A detailed analysis of selected decisions of the International Criminal Tribunal for the former Yugoslavia and the International Criminal Tribunal for Rwanda demonstrates that these tribunals could not simply rely on classical sources of public international law to resolve difficult cases. Further, the experimental approach taken to recasting these sources of law in Article 21 of the Rome Statute of the International Criminal Court has not resolved fundamental tensions inherent in the international criminal law tradition. Both at the modern ad hoc tribunals and in the Rome Statute, it is argued that difficult cases are decided based on a highly discretionary selection by judges between two competing norms. On one hand, there is the need to enhance humanitarian protection during armed conflict, an ideal embedded in international humanitarian law and particularly the Martens Clause. On the other hand, there is the aim of maximizing fairness to the accused, an ideal enshrined in the growing body of international human rights law and codified in Article 21(3) of the Rome Statute. This article seeks to illuminate these fundamental tensions within the international criminal law jurisprudence at a foundational moment when the ICC begins hearing its first set of cases.

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)0.136
metaresearch head score (Gemma)0.283
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: Empirical · Consensus signal: none
Teacher disagreement score0.136
Threshold uncertainty score0.718

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1360.283
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0260.082
Scholarly communication0.0440.032
Open science0.0070.017
Research integrity0.0190.021
Insufficient payload (model declined to judge)0.0040.001

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 head0.080
GPT teacher head0.349
Teacher spread0.270 · 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
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

Citations2
Published2008
Admission routes1
Has abstractyes

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