Bibliographic record
Abstract
The present work is chapter 1 of the edited volume, Torture as Tort: Comparative Perspectives on the Development of Transnational Human Rights Litigation (Hart Publishing, Oxford, 2001). At the time the book was generated, the controversial nature of seeking globalised justice through national courts had become starkly apparent in the wake of the Pinochet case in which the Spanish legal system sought extradition of the former President of Chile from the United Kingdom in order to bring him to account under Spanish criminal law for a variety of alleged violations in Chile of human rights, most notably involving torture. Yet, the international legal and associated statutory bases for such criminal prosecutions were both well understood in legal doctrine and well entrenched in many states’ legal systems, in comparison to transnational civil liability for human rights violations. This book set out to address the civil liability side of accountability for human rights violations.\nWhen Torture as Tort was published, there had been very little treatment, let alone a comprehensive assessment, of the merits and demerits of US-style transnational human rights litigation by non-American legal scholars and practitioners. The book seeks not so much to fill this gap as to start the process of doing so, with a view to stimulating debate amongst scholars and policy-makers. The volume consisted of 26 chapters divided into six thematic parts, written by 30 scholars (all non-American); the table of contents is reproduced at the end of this abstract. The objective of the book was, and remains, to generate doctrinal, theoretical, and policy-relevant inquiry over the question of the feasibility and legitimacy of transnational human rights litigation.\nThe present “Introduction to Torture as Tort: From Sudan to Canada to Somalia” consists of a narrative and analytical roadmap of the topics covered and arguments developed in the 25 chapters that follow the present one. It is organized into sub-sections that correspond to each thematic Part in the book (again, see the table of contents reproduced below). After this roadmap, an additional subsection places the overall book project into the concrete context of the first tort case to come before a Canadian court that involves allegations of torture in another country, Arone v. Canada.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.023 | 0.002 |
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".