Bibliographic record
Abstract
Le nazisme a initié la systématisation de la terreur dans le cadre du génocide des Juifs : violences sur les civils, mutilations, désintégration des corps, disparition des restes. Les terroristes développent eux aussi la stratégie de la terreur totale, ajoutant aux victimes des attentats (blessés et morts), celles du traumatisme (les survivants et les endeuillés). Il ne s’agit donc plus seulement de tuer, mais aussi d’organiser l’horreur par la violence, l’aspect aléatoire de la mort, l’innocence des victimes. Cette hypothèse est vérifiée par le nombre de deuils post-traumatiques qui en découlent. L’absence de corps ou leur destruction empêchent une phase essentielle du travail de deuil : la prise de conscience de la réalité puis l’acceptation de la mort. Seule la vengeance peut émerger d’autant de douleur. Mais n’est-ce pas la menace du terrorisme : développer la spirale mortifère d’une guerre de position basée sur la rétorsion ?
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.028 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".