Bibliographic record
Abstract
Peut-on encore se dire « communiste » après le goulag ? La question anime et divise celles et ceux qui ne se résignent pas à l’ordre capitaliste et à son cortège d’injustices. La crise de 2008 a suscité un intérêt renouvelé pour la pensée de Karl Marx, a ravivé la lutte des classes et a redonné du crédit aux thèses anticapitalistes. La jeune génération militante, qui se mobilise contre l’austérité, contre le racisme, contre le sexisme et pour le climat, lutte pour une société qu’elle ne sait comment nommer. Est-ce ici un désir de communisme qui refait surface ? Peut-on revivifier l’idéal communiste en passant outre les régimes qui l’ont incarné (ou ont prétendu l’incarner) au siècle passé ? Manuel Cervera-Marzal a posé ces questions à quatorze figures majeures de la pensée critique contemporaine : Alain Badiou, Etienne Balibar, Pierre Dardot, Alain Deneault, Bernard Friot, Christian Laval, Chantal Mouffe, Irène Pereira, Michel Pinçon, Monique Pinçon-Charlot, Michèle Riot-Sarcey, Françoise Vergès, Sophie Wahnich et Slavoj Zizek. Il en résulte un ouvrage polyphonique, qui est un espace de débat, accueillant aussi bien des textes qui proposent de réhabiliter le « communisme » que des points de vue plus sceptiques sur une telle opération.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.024 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.006 |
| 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".