Between the Devil and the Deep Blue Sea—Towards Access to Justice for Local Communities in Investor-state Arbitration or Business and Human Rights Arbitration
Bibliographic record
Abstract
This article focuses on the proposal to adapt international arbitration to business disputes involving human rights. The Business and Human Rights arbitration (BHR arbitration) proposal seeks to give local communities who are victims of multinational corporations’ human rights and environmental abuses access to justice in a specialized international BHR arbitration tribunal. Through a comparison between investor-state arbitration (ISA) and BHR arbitration, this article contends that it would be more efficient to reform ISA than to create a BHR arbitration tribunal. Reforming ISA would avoid the possible parallel arbitration systems that may arise from the duplication of international governance efforts. It would also reduce local communities’ need to resort to transnational litigation, which is procedurally complex and often unsuccessful. Therefore, the possibility of ISA reform makes the BHR arbitration proposal superfluous or, at best, limited in its potential application. Creating a new arbitral structure that is untested and fraught with procedural and substantive complexities may not be worth the trouble. Considering the parallels between the ISA and proposed BHR arbitration, and the prospect of creating a one-stop shop for business and human rights abuse, this article suggests that BHR arbitration is an unnecessary governance effort in international arbitration and a distraction from necessary ISA reform.
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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 | 0.013 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.040 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.001 | 0.021 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
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".