Bibliographic record
Abstract
Véronique Jago-Antoine, dans « “Je ne lis pas avec sagesse” : réflexions en marge de la bibliothèque du poète Odilon-Jean Périer », explore le potentiel pour la recherche des bibliothèques d’écrivains, à partir du cas de la bibliothèque du Fonds Odilon-Jean Périer, poète bruxellois. En croisant sa bibliothèque avec son œuvre, sa correspondance, ses œuvres graphiques et picturales, l’article met lumière les apports que les bibliothèques peuvent apporter à la compréhension du travail de l’écrivain. Ainsi, l’article montre d’abord dans le cas de Périer, en quoi sa bibliothèque, sur le mode d’une transaction relationnelle, l’affirme comme poète moderniste, puis met en lumière l’influence des juvenilia qui y sont conservés sur son œuvre, puis ce que l’étude d’exemplaires multiples peut apporter. Enfin, à partir de l’étude de l’exemplaire le plus annoté, il montre sa proximité théorique avec Max Jacob.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".