Bibliographic record
Abstract
L'extrême-gauche plurielle. Entre démocratie radicale et révolution, Philippe Raynaud, Paris, Ed. Autrement, 2006, 206 p. Si le candidat d'extrême-droite Jean-Marie Le Pen a pu participer au deuxième tour de l'élection présidentielle d'avril 2002, c'est entre autres, assez paradoxalement, parce que des candidats d'extrême-gauche avaient grugé suffisamment de voix au candidat socialiste Lionel Jospin pour l'empêcher d'aller au-delà du premier tour. Comparée aux autres démocraties libérales, la France aurait donc un profil atypique, non pas du fait de la force, chez elle, de l'extrême-droite (celle-ci est aussi très présente dans beaucoup d'autres pays européens), mais plutôt du fait de la présence d'une “ gauche de la gauche ” qui recueille un nombre significatif de voix et a un poids certain dans la vie politique du pays.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".