Grand corps et mini-États ou l’image d’un tout ce que nous sommes en Tunisie
Bibliographic record
Abstract
Cet article traite de deux questions principales : le corps et l’État. L’auteur prend le cas de figure d’un spectacle de danse qui était produit et diffusé au cours des années 1990 en Tunisie. Intitulé « Nouba », ce spectacle fournit les appuis empiriques nécessaires pour que l’idée faisant de l’État un Grand Corps et du corps un mini-État ne se limite point à la métaphore, mais s’attache plutôt à la réalité. En effet, cette idée a permis à l’auteur d’appréhender le pays et le spectacle l’un à la lumière de l’autre, tout en portant l’analyse hors des sentiers battus. Cela dit, le fait que l’article traite de la question du corps dans une société arabo-musulmane ne l’implique pas automatiquement dans la sphère des études orientalistes ou islamologiques. Autrement dit, ce n’est pas de l’interdit que l’on discute dans ce texte, mais plutôt de l’inter-dit.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".