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Record W3135449618 · doi:10.2307/j.ctv1h0p2k0

Forum non conveniens, une impasse pour la responsabilité sociale des entreprises?

2020· book· fr· W3135449618 on OpenAlexaboutno aff
Ivan Tchotourian, Alexis Langenfeld

Bibliographic record

VenuePresses de l'Université Laval eBooks · 2020
Typebook
Languagefr
FieldBusiness, Management and Accounting
TopicCorporate Law and Human Rights
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Le débat est animé concernant les entreprises multinationales qui bafouent les droits de l’homme lors de leurs activités à l’étranger et la question de l’accès de leurs victimes aux tribunaux est récurrente. Bien qu’elles soient centrales lorsqu’un procès est envisagé, les règles de procédure, techniques par nature, sont souvent reléguées au second plan. Il en va ainsi du forum non conveniens , une doctrine selon laquelle un juge canadien compétent peut renvoyer un litige devant le tribunal du pays hôte. Or, cette doctrine est problématique relativement à la responsabilité des entreprises multinationales : si la justice ne peut être rendue, la responsabilité sociétale des entreprises n’est-elle pas qu’un miroir aux alouettes au Canada ? \n \nCet ouvrage présente la doctrine du forum non conveniens de manière historique, synthétique et critique et revient sur l’actualité entourant le phénomène de judiciarisation de la responsabilité sociale des grandes entreprises, tant au Canada qu’aux États-Unis et en Europe. En exposant les plus récentes décisions judiciaires canadiennes dans ce domaine, cet ouvrage démontre que les juges ont tendance à accueillir plus favorablement les victimes étrangères dès lors que la responsabilité extracontractuelle d’une entreprise multinationale pour des violations des droits de l’homme est invoquée.

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)0.008
metaresearch head score (Gemma)0.011
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: Other · Consensus signal: Other
Teacher disagreement score0.067
Threshold uncertainty score0.133

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0190.033
Scholarly communication0.0130.014
Open science0.0020.007
Research integrity0.0070.007
Insufficient payload (model declined to judge)0.0110.001

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 head0.013
GPT teacher head0.192
Teacher spread0.180 · 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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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