Bibliographic record
Abstract
Qu’est-ce que la liberté ? Qu’est-ce que l’égalité ? En quoi une plus grande égalité peut-elle accroître la liberté ? Telles sont les questions principales auxquelles tente de répondre cet article. Le problème du choix entre liberté et égalité soulève en effet le problème de la définition de ces deux objets. Une fois cette définition clarifiée, il ressort que, sous certaines conceptions de la liberté et de l’égalité, il n’est pas nécessaire ou utile de choisir entre ces deux objets : ils deviennent alors complémentaires plutôt que substituts. L’égalité peut en effet renforcer à la fois la liberté réelle et la liberté morale des individus, et ainsi contribuer au bien-être de tous. L’article traite aussi des difficultés de mesure de l’égalité, et en quoi ces difficultés peuvent affecter la comparaison de l’égalité à travers le temps et l’espace.
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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.027 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 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".