L’égalité, le possible et ce que les «hommes devraient “pouvoir être”» : sur <i>La gauche et l’égalité</i> de Jean-Michel Salanskis
Bibliographic record
Abstract
RÉSUMÉ : La gauche et l’égalité de Jean-Michel Salanskis cherche à faire le bilan des principes traditionnels de la gauche afin de la guérir de certaines illusions et de renouveler ce qui est, pour lui, son pilier central : la quête de l’égalité. Mais pour ce faire, il déploie un concept de possibilité ambigu et problématique qui pourrait mettre en péril la cohérence de son projet. La présente étude analyse le texte de Salanskis en décortiquant son concept de possibilité, et propose quelques ajustements afin d’éviter certains écueils classiques dans l’histoire de la pensée dialectique.
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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 | 0.001 |
| Science and technology studies | 0.007 | 0.017 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".