Bibliographic record
Abstract
Is violence ever warranted, and if so, under what circumstances? The acceptability of deterrence and sacrifice to forestall further violence in an open, transparent, society depends on persuasion and the freedom to argue vigorously over the use of such violence. The debate in Sallust’s Bellum Catilinae between Caesar and Cato over the execution of the Catilinarian conspirators (51–52) and the debate in the Aeneid between Drances and Turnus over the vast carnage that could be averted if only Turnus would sacrifice himself (11.336–446) illustrate the principle that utilitarian violence depends upon persuasion. N’y a-t-il jamais de justification à la violence et, si oui, en quelles circonstances ? La légitimation du châtiment dissuasif et du sacrifice pour prévenir une montée de violence dans une société ouverte et transparente dépend de la persuasion et de la liberté d’argumenter vigoureusement contre l’usage d’une telle violence. Le débat dans le Bellum Catilinae de Salluste entre César et Caton au sujet de l’exécution des conjurés catilinariens (51–52) et le débat dans l’ Énéide entre Drancès et Turnus à propos du vaste carnage qui pourrait être évité si seulement Turnus consentait à se sacrifier (XI, 336–446) illustre le principe que la violence utilitaire dépend de la persuasion.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.009 | 0.018 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".