Que devient le récit de filiation au Québec ? Exemples d’Éric Dupont et de Nicolas Dickner
Bibliographic record
Abstract
crite en franais, mais amricaine par son esprit, la li rature qubcoise a rsist dans son ensemble aux tenta ons du nouveau roman dont l'essoufflement aurait t un des s mules de l'mergence des rcits de filia on en France 1 . Elle n'a pas pour autant chapp la transforma on du roman familial qui sous-tend certains genres tradi onnels comme le roman du terroir et plus tard le roman de la ville. L'volu on sociale et culturelle des dernires dcennies, l'irrup on et l'intgra on de la li rature migrante dans le canon li raire qubcois transforment les caractris ques communautaires de ce e li rature, y compris le roman familial. Peut-on alors parler du rcit de filia on qui serait en mme temps une histoire individuelle et, travers elle, une recons tuon, par fragments recomposs, de l'h/Histoire ? L'analyse de deux ouvrages rcents, Nikolski (2007) de Nicolas Dickner et La Fiance amricaine (2012) d'ric Dupont, perme ra de dgager les traits caractris ques de ces approches scripturales.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.025 | 0.011 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".