Bibliographic record
Abstract
Abstract Punitive practices are highly revealing of a society’s social fabric, normative order, and power structure. The social sciences and humanities have studied punishment mostly in the context of the nation-state by examining how people, organizations, and legal institutions punish individual offenders. This book examines the penal philosophies and practices of a society that has barely been approached from such a perspective: international society. The chapters in this book show the added value of a punitive lens to international politics in at least two ways. First, punitive practices reveal the contours of the international normative order, its structures, and its hierarchies. Such a perspective highlights the prominent position of individuals in the current normative order, but it also reveals a major cleavage in the international normative order between a Global North that emphasizes individualized, retributive punishment for atrocity crimes, even if implemented highly selectively, and a Global South that puts reparations for past colonial wrongs on the agenda. Second, in contrast to a nation-state, the authority to sanction and thus to act in defense of the normative order is far more dispersed and contested in international society. Although there is a demand to embed punitive practices in procedures and institutions, the most legitimate site of such authority remains contested as regional organizations such as the African Union compete with the United Nations for the authority to sanction and act in defense of the normative order.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 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".