Corporate Voluntarism and Human Rights: The Adequacy and Effectiveness of Voluntary Self-Regulation Regimes
Bibliographic record
Abstract
In response to increasing public concern over the accountability of transnational corporations (TNCs) for violations of human rights in the states in which they operate, governments, corporations and NGOs have promoted the development and implementation of voluntary self-regulatory regimes. However, TNC practices under these regimes call into question their adequacy and effectiveness in preventing complicity in egregious violations of human rights by corporations operating in conflict zones and repressive regimes. This article reviews and assesses the language, human rights content and compliance mechanisms of the voluntary policies and/or codes developed by a number of corporations, industry groups, intergovernmental organizations and multi-stakeholder initiatives, as well as associated corporate practices. The analysis shows that these voluntary regimes are flawed and inadequate, and therefore unable to ensure that TNCs are not complicit in human rights violations in their extraterritorial activities.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".