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Record W7010624386

International & Transnational Criminal Law

2013· article· en· W7010624386 on OpenAlexaboutno aff

Bibliographic record

VenueeYLS (Yale Law School) · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Bioinformatics, and Biomedical Research
Canadian institutionsnot available
Fundersnot available
KeywordsCriminal lawWar crimeJurisdictionUniversal jurisdictionInternational lawHuman rightsOrganised crime
DOInot available

Abstract

fetched live from OpenAlex

International criminal law has focused on the prosecution of truly international crimes — genocide, crimes against humanity, war crimes, and aggression. Our post-Cold War, post-9/11 world has also seen the growth of transnational crimes of international concern, such as terrorism, money laundering, organized crime, and human and narcotics trafficking, as well as transnational crimes of domestic concern, which are simply ordinary domestic crimes that involve the jurisdiction of more than one state. This book surveys these two related but increasingly distinct fields with a focus on Canada, bringing together in one accessible text topics that are of increasing importance in a world of globalized crime. The second edition updates caselaw from Canada as well as international courts and tribunals, transnational criminal law treaties, and recent literature, and adds a new chapter on extended liability, defences, and child soldiers. It reviews the new definition of the crime of aggression and some of Canada's new criminal cooperation ventures.

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.277
Threshold uncertainty score0.551

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0060.004
Scholarly communication0.0110.004
Open science0.0010.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0610.018

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 head0.019
GPT teacher head0.282
Teacher spread0.262 · 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
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
Published2013
Admission routes1
Has abstractyes

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