The Antinomies of Legitimacy: On the (Im)possibility of a Legitimate International Criminal Court
Bibliographic record
Abstract
This paper critically analyzes the concept of legitimacy as it applies to international criminal law. Using the referral of the situation in Darfur to the International Criminal Court ( icc ) – and the resultant disagreement between Sudan, the African Union, and the icc – as an entry point, it examines the discourse about the referral as a contest of legitimacy. After placing this specific example in the context of theories of legitimacy, it argues that there are no objective criteria for determining the legitimacy of an international criminal tribunal. Legitimacy as a concrete concept is best understood as a Kantian antinomy – an unanswerable question that borders on the metaphysical. Yet this indeterminacy can be turned to the advantage of the critical theorist, offering pragmatic, normative, and pluralist alternatives for the reconstitution of international criminal tribunals such as the icc .
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".