Bibliographic record
Abstract
Cet article explore la transformation possible de la colère – une émotion – en indignation ou bien outrage – une passion sociale. Se pose ici la question de savoir quand et comment finissent les émotions. On considèrera le rôle attribué à la revanche (Aristote) et au ressentiment (Max Scheler). Cette transformation est traitée à travers l’expérience des harkis, ces Algériens qui prirent le parti des Français durant la guerre d’indépendance d’Algérie, et qui furent massacrés par dizaines de milliers par la population algérienne à travers le pays à l’issue de la guerre. La colère des harkis, abandonnés par les Français, est médiatisée par le sens d’un destin : celui-ci n’est pas partagé par leurs enfants, qui souffrent des blessures des pères sans les connaître exactement, à cause du silence de ces derniers. Pris dans la douleur de leur propre expérience, les enfants vivent ainsi un double traumatisme. En retrait de l’expérience directe, leurs récits et leurs revendications politiques attisent la colère qui sous-tend leur indignation. Y a-t-il une issue? C’est la question que l’on se pose.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.026 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 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".