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Record W7008438004

Canadian Corporations Bound by the Phoenix: Setting the Path for the United States

2022· article· en· W7008438004 on OpenAlexaboutno aff

Bibliographic record

VenueEngagedScholarship @ Cleveland State University (Cleveland State University) · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Law and Human Rights
Canadian institutionsnot available
Fundersnot available
KeywordsSupreme courtOriginal jurisdictionJurisdictionLiabilityInternational lawCustomary international lawPrecedentCommon law
DOInot available

Abstract

fetched live from OpenAlex

This Note argues that the United States courts have jurisdiction to consider corporate liability for international law violations of human rights under the reasoning of the Supreme Court of Canada, in Nevsun Resources Ltd. v. Araya. The United States Supreme Court has escaped holding such liability exists, but Canada has outlined how countries, such as the United States, no longer can avoid holding corporations liable under customary international law. Corporate liability for human rights violations committed abroad is a cutting-edge issue. The United States Supreme Court has considered the issue before, but the Court used different analyses and was without any precedent to refer to. In prior decisions, the Court rationalized that customary international law was not influential enough and that Congress needed to be involved to hold corporations liable for such violations. However, the Supreme Court of Canada’s decision demonstrates that the United States’ justices who previously decided against adoption of corporate liability under customary international law no longer can defend their antiquated arguments. This issue is bound to be in front of the Court again and will be highly publicized because of the trending rise of importance of human rights. The United States Supreme Court must conform to the customary international law holding corporations liable for international law violations of human rights.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.432
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0190.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.023
GPT teacher head0.184
Teacher spread0.161 · 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 teacher head, not a consensus.

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

Citations0
Published2022
Admission routes1
Has abstractyes

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