Bibliographic record
Abstract
I lie poome de Macie-Chi« B",cquacr' appelle a un ,""emblement L de toutes nos facultes d'accueil afin de penetrer l'intense mobilite ~de cette ecriture qui se deplace d'une fa<;:on etonnante, de la marge au texte, dans une presence qui ne peut qu'echapper a une lecture detournee.11 y a dans cette poesie une force et un elan qui savent nous engager ou nous detacher, selon que I'on accepte ou pas la chronique des evenements d'une interiorite qui ne se menage jamais.Lecriture de Marie-Claire Bancquart est sans concession, ni au langage, ni au sens.Le poete brule dans la douleur, pas seulement celle que I'on pressent sienne mais dans la douleur endemique du monde.Ici, il semblerait que cette douleur ne soit pas seulement la mort avec sa finalite acceptee qui peut reduire les angoisses et les peurs.« Pourquoi naZtre?et pourquoi suis-je nee? ».C'est la force de cette si intime question a laquelle
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.056 | 0.018 |
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".