Bibliographic record
Abstract
This article explores the manner in which the logic of the war crimes trial authorizes and legitimates the practice of war more generally. It proceeds from the recognition that all war involves injuring or the threat of injuring, and that articulating particular types of injuring as especially problematic takes as one of its effects the normalization of injuring in war more generally. The article queries the function of law through an analysis of the state of exception that is produced in the identification of 'war crimes'. It argues that the logic of excision, which produces the political conditions in which war crimes become possible is structurally replicated through the excision of the perpetrator in the context of the trial. It also explores the manner in which the narrative strategies of what Elaine Scarry calls 'active redescription' associated with war render most war-related deaths and injuries politically invisible. The article concludes with a number of strategies for rethinking what it means to account for violence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.061 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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".