In the face of epistemic injustices?: on the meaning of people-led war crimes tribunals
Bibliographic record
Abstract
This paper seeks to render intelligible the meaning of the vibrant tradition of people-led war crimes tribunals (PWCTs) which has emerged in the past half a century. Drawing upon recent postcolonial critiques of extant literature on geographies of care and responsibility, and informed by Third World Approaches to International Law (TWAIL), we question the capacity of the international legal system to provide justice for ‘others’ (especially subaltern and colonised communities) at a distance. We situate PWCTs in the context of the claim that the international legal system is systemically contaminated because it is conceptually Western. We interrogate the seminal Russell Tribunal on Vietnam (1966–67) and in so doing are led to place under scrutiny the postcolonial and dialectical ethics which characterised the work of French philosopher, literary giant, and political activist Jean-Paul Sartre before, during, and after his tenure as Executive President of this tribunal. We argue that insofar as PWCTs speak subaltern truth to power, they work to decentre the Western ethical, legal, and juridical canon and confront insidious epistemic injustices. We conclude that any search for a postcolonial ethics to guide caring from afar can both inform and be informed by PWCTs.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.072 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".