Vision-Division L'oeuvre de Nancy Huston
Bibliographic record
Abstract
Canadienne, Parisienne, musicienne, écrivaine de renommée internationale, Nancy Huston séduit aussi bien par ses essais provocateurs que par ses romans audacieux. Vivant entre deux langues et deux cultures, elle a conquis tant les publics francophone qu’anglophone. La narratrice d’Instruments des ténèbres formule cette phrase troublante: « Pas de vision sans division. Je ne cesse de comparer, combiner, séduire, traduire, trahir. J’ai le coeur et le cerveau fendus, comme les sabots du Malin. Anglais, francais. » C’est avec cette citation comme point de départ que cet ouvrage propose une vision de son écriture centrée sur le dédoublement et la duplicité: des auteurs en provenance de nombreux pays présentent une oeuvre ou priment les thèmes de l’exil et de l’enfermement, de la musique et de la folie, de l’enfance et de la vieillesse, sous la plume d’une écrivaine qui, selon le Magazine littéraire, compte au nombre de ceux « qui ne cessent de detruire pour mieux pouvoir reconstruire. »
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".