Against Settlement in Transnational Business and Human Rights Litigation
Bibliographic record
Abstract
In Against Settlement, Owen Fiss argued that settlement may not always be the optimal result of civil suits, particularly those that involve novel or ambiguous areas of law or ostensible power imbalances. That work spurred a range of scholarship around the merits and demerits of settlement. And although the settlement versus litigation debate is now almost four decades old, its currency persists in common law systems in which courts are, at times, called upon to expand or even re-envision doctrines or procedural rules. This article revisits that debate. It applies Against Settlement to transnational business and human rights litigation that has, over the past few decades, resulted in a number of high-profile civil claims across the common law world. In the context of that area of litigation, adjudication on the merits of a claim has benefits beyond the specific litigants involved. I focus on three transnational business and human rights case studies, all of which affirm one or more aspects of Fiss’s argument that the notion of settlement as a systemic solution ought to be challenged. First, I address how the October 2020 settlement in Araya v. Nevsun Resources Ltd. further obscures what continues to be a murky intersection of customary international law and Canadian common law. Second, I look at U.K. litigation around Barrick Gold’s labour practices in East Africa. In that instance, settlement has been ineffectual to stop the mining giant from continuing to engage in harmful practices that contribute to personal and environmental harm. And third, I discuss how the settlement in Garcia v. Tahoe Resources Inc. is an example of transnational corporate defendants side-stepping accountability when they settle out of court, even if they publicly acknowledge wrongdoing. The case studies suggest that Fiss’s argument remains relevant and, to the extent it can be operationalized, it should be taken seriously, despite the fact that ADR mechanisms have become a panacea on how to fix problems associated with state-based judicial dispute resolution processes.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".