Impact on Remedies of the Use of Corporate Governance Norms to Address Forced Labour
Bibliographic record
Abstract
Forced labour, a pervasive issue within transnational production networks (TPNs), has been the subject of regulatory responses primarily centred around the use of corporate governance norms. These norms, whether through disclosure or due diligence laws, or in some common law countries, litigation seeking judicial recognition of a common law duty of care, are the sole legal mechanisms linking lead corporations to the working conditions in their TPNs. This article critically evaluates the potential of these corporate governance norms to provide effective remedies to forced labour workers, a topic of significant importance as it recognizes their agency rather than portraying them as passive victims.To this end, this article will appraise two legislative models, one implementing disclosure and the other due diligence, while examining the duty of care jurisprudential model, from the procedural and substantive criteria of effective remedies: the California Transparency in Supply Chains Act (CTSCA) disclosure regulation, the French vigilance law, and the Canadian common law duty of care. The analysis underlines a few, primarily procedural, improvements generated by disclosure and due diligence legislation, as well as the common law duty of care toward more effective remedies. These corporate governance norms increase available information and foster accessibility to some extent. However, substantive improvements brought by corporate governance norms are either constrained (France), hypothetical (Canada) or non-existent (California). Moreover, the corporate governance norms examined fail to provide effective judicial remedies for forced labour victims and may undermine potential lawsuits by providing corporations with a defence. We conclude with a discussion of the newly adopted German and Canadian laws.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".