Bibliographic record
Abstract
Si ma vie etait un roman, quelqu'un (peut-etre moi) la mettrait par ecrit, et cette aventure y tronerait, et un certain veloute de la peau y serait celebre dans le vocabulaire le plus satine qui soit. Et tout aurait enfin un sens, meme ce qui me chagrine. Couples, amis, parents et enfants, voisins, collegues, amants et inconnus, tous les protagonistes, narrateur compris, s'assemblent et s'additionnent dans ce qui n'est pas assez, ou deja plus, trop ou trop peu. Au lieu-dit desmalaises muets, le reel repand ses largesses : rivalite, tromperie, meprise, mensonge, humiliation, imposture, ignorance, incommunicabilite... Parce qu'il a besoin de sentir palpiter la vie « dans une forme dont le pouls est si evidemment rapide », l'ecrivain choisit la nouvelle breve : dense, exigue, concentree, rusee, epicee, mordante, fine dans l'humour autant que dans l'emotion. En soixante-six textes, il puise sans relâche dans le rapport de force entre l'imponderable et l'intelligence des mots. Apres i (i trema), qualifie d'œuvre etonnante, recipiendaire du Prix litteraire Ville de Quebec/Salon du livre et traduit a l'etranger, Gilles Pellerin nous revient avec i2 (i carre), son sixieme recueil de nouvelles. Il croit plus que jamais que la litterature est ce qu'on ajoute a l'univers. Pour le plus grand plaisir du lecteur.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.150 | 0.092 |
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".