Research Note: Rawls Revisited: Can International Criminal Law Exist?
Bibliographic record
Abstract
Abstract.Questions concerning how Rawls's theory of justice accords with international criminal justice are largely ignored in favour of extensive debates on questions of distributive justice and how they relate to his theory and its international application. This lack of attention to international criminal law is significant since Rawls claims that his theory of justice is developed to correspond with recent dramatic shifts in international law. This paper argues that it is impossible for Rawls's account, state-centric as it is, to accord with advancements in international law that have increasingly asserted recognition of individuals in the global context. Résumé.Les questions concernant comment la théorie de justice de Rawls est en accord avec la justice criminelle internationale sont en grande partie ignorée, même pendant qu'en même temps sa théorie et son application internationale sont profondement discutée par rapport à la justice distributive. Ce manque d'attention à la loi criminelle internationale est important, puisque Rawls prétende que sa théorie de justice est développée en correspondance avec les récents changements dramatiques au niveau de la loi internationale. Cette exposé argumente qu'il est impossible que l'explication de Rawls, état-centré comme elle l'est, s'accorde avec les avancements en la loi internationale qui affirment de plus en plus la reconnaissance des individus dans le contexte global.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.006 | 0.028 |
| Scholarly communication | 0.013 | 0.021 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.019 | 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".