‘Global South’ Voices Are Muted in Debates over the Crime of Aggression: What Three Books on Illegal War Tell Us About Why
Bibliographic record
Abstract
Political and legal efforts to criminalize illegal warfare have received a tremendous amount of attention since the 2002 establishment of the International Criminal Court (ICC). At no point have discussions on the crime of aggression reached such feverish levels as they did following the 2022 invasion of Ukraine by Russian forces. Ongoing debate over how to investigate and prosecute the invasion, alongside the relatively muted response of the global South to a proposed specialized tribunal to prosecute Russian leaders for the crime of aggression, is symptomatic of how diplomats have crafted the crime over the past two decades. Those negotiations – their reasoning, political contours, historicity and consequences – have been studiously covered by Carrie McDougall, Tom Dannenbaum and Noah Weisbord in their respective books on the crime of aggression. Theirs are persuasive volumes written by thoughtful and diligent scholars of international criminal law (ICL). The books offer detailed assessments of what the crime is, its historical trajectory, its adoption and particular jurisdictional shape under the Rome Statute, as well as the role it might play in moderating international relations’ most devastating excess: war. Each author speaks to the politics of law and, to put it crudely, how the proverbial sausage – international law in this case – is made. The books articulate with laudable finesse how the crime of aggression came to be what it is today. This is, at times, a grim task, and the disappointment of the authors at the neutered version of the crime of aggression included under the Rome Statute is apparent. At the same time, these volumes, which also offer much hope, include lessons for the law student, diplomat and negotiator on how negotiations capture particular cross-sections in time and politics.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.025 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".