Surya Deva, Regulating Corporate Human Rights Violations, New York, Routledge, 2014
Bibliographic record
Abstract
Le Conseil des droits de l’homme de l’ONU a approuve, le 26 juin 2014, un projet de resolution qui elaborera la definition de normes contraignantes pour les multinationales en matiere de droits humains. L’adoption d’une telle resolution est une avancee sans precedent en ce qui concerne l’elaboration des normes contraignantes pour les multinationales. En effet, il n’existe actuellement aucun instrument juridiquement contraignant au niveau international qui possede un « mecanisme de sanction pour reguler et controler les impacts des multinationales sur les droits de l’homme et assurer l’acces des victimes a la justice ». Qui plus est, il s’agit d’une occasion inestimable afin de mettre fin a l’impunite qui regne en faveur des entreprises multinationales. Ainsi, considerant l’impunite dont trop d’entreprises transnationales ont profite, il est opportun de se demander s’il est possible d’elaborer de nouvelles normes internationales contraignantes afin d’assurer le respect des droits humains par les societes transnationales.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.010 | 0.011 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.012 | 0.009 |
| Insufficient payload (model declined to judge) | 0.038 | 0.008 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".