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Record W2080257952 · doi:10.1093/jicj/mqq021

Corporate Civil Liability for War Crimes in Canadian Courts: Lessons from Bil'in (Village Council) v. Green Park International Ltd.

2010· article· en· W2080257952 on OpenAlexaboutno aff
Josef T. Yap

Bibliographic record

VenueJournal of International Criminal Justice · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Law and Human Rights
Canadian institutionsnot available
Fundersnot available
KeywordsLiabilityLawPolitical scienceCriminal liabilityCriminal courtSpanish Civil WarEconomic JusticeWar crimeInternational lawCriminal law

Abstract

fetched live from OpenAlex

In many cases of alleged war crimes, a civil action may be an attractive alternative to criminal proceedings, for political, logistical or other reasons. This is particularly so with respect to corporate conduct, where the mens rea requirements and custodial penal sentences that are hallmarks of typical criminal justice systems transpose poorly to the corporate context. However, while the universality principle is by now well-established with respect to criminal prosecutions in national courts, the picture with respect to civil claims in one country for war crimes committed in another is substantially less clear. In this spirit, the author analyses the recent Superior Court of Quebec decision in the case of Bil’in (Village Council) v. Green Park International Ltd. There, the plaintiffs sought to claim against two Quebec corporations and their sole director for participating in war crimes allegedly committed in the West Bank. After a careful examination of the decision, it becomes apparent that such claims may face significant legal and practical hurdles in Canada.

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)0.020
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 score0.211
Threshold uncertainty score0.915

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.007
Science and technology studies0.0210.010
Scholarly communication0.0120.005
Open science0.0040.003
Research integrity0.0080.007
Insufficient payload (model declined to judge)0.0060.000

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 head0.063
GPT teacher head0.278
Teacher spread0.215 · 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
Published2010
Admission routes1
Has abstractyes

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