Bibliographic record
Abstract
L'analysant l'apprend tôt ou tard : l'enfance ne se raconte pas. Il n'y a pas de mots propres pour la dire. L'oubli qui la recouvre n'est sans doute pas à comprendre en tant qu'effet de la censure et du refoulement, mais plutôt comme la conséquence d'une incompréhension foncière, d'un abandon de la mémoire devant ce qu'elle n'a pas pu saisir faute de mots, de mots qui jamais ne nous appartiennent tout à fait, fussent-ils ceux de l'autre en nous. Dans toute son oeuvre, Julien Bigras a donné à l'enfance sa valeur transférentielle, la faisant lieu d'un véritable investissement, très proche du transport amoureux, et non l'assise d'une commode référence. Particulièrement dans Ma vie, ma folie (1983), roman autobiographique à deux voix, il fait du « chagrin d'enfant » l'histoire insue de signifiants en délire autour desquels Docteur Bigras et sa patiente Marie construisent leur énonciation spéculaire.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.010 | 0.014 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.016 | 0.005 |
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".