Mireille Calle-Gruber ou les promesses de la littérature et des arts Mireille Calle-Gruber or the promises of literature and the arts
Bibliographic record
Abstract
C’est à Mireille Calle-Gruber que ces deux journées veulent rendre hommage en rassemblant artistes, écrivains, intellectuels, amis, collègues, chercheurs et étudiants qui l’ont accompagnée. Mireille Calle-Gruber œuvre en tant que professeur et en tant qu’écrivain dans la langue française depuis la connaissance et l’expérience des cultures autres. Son travail est pluriel et transfrontalier : il traverse les grammaires et fait migrer les disciplines. Il dissémine les savoirs et décloisonne la recherche. Son séminaire ouvre un espace-temps où l’impensable est accueilli. Où l’impossible arrive. Passeuse des œuvres, amie des artistes, Mireille Calle-Gruber nous fait le don des promesses de la littérature, et c’est à nous qu’il revient de faire perdurer cet héritage.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.170 | 0.042 |
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".