Bibliographic record
Abstract
La notion d'exclusion est généralement employée comme un mot-valise qui recouvre les situations les plus hétérogènes. Surtout, elle concentre l'attention sur les situations extrêmes d'individus et de groupes placés en dehors de la sphère des échanges sociaux réglés. Elle présente ainsi un double piège, pour la réflexion sociologique et pour l'action politique. Pour la réflexion, elle conduit à faire l'impasse sur les processus qui, en amont de ces situations, l'alimentent: précarisation des rapports de travail, fragilisation des supports de la sociabilité... Pour l'action, elle induit principalement des pratiques d'assistance et de réinsertion qui, si elles sont indispensables dans une conjoncture dégradée, ne doivent pas servir d'alibi pour économiser des interventions préventives sur les dynamiques de déstabilisation de la société salariale.
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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.040 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.014 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.010 | 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".