Dante au Quebec. Lecture critico-genetique de l’ «Enfer mis en vulgaire parlure» d’Antoine Brea
Bibliographic record
Abstract
Antoine Brea, a Parisian novelist and jurist born in 1975, chose Québec as the ideal publishing context for his bold translation of Dante’s Inferno, L’Enfer de Dante mis en vulgaire parlure (Le Quartanier, 2021). As the first French version published out- side Europe, this work represents a radical departure in the Francophone reception of Dante. An expression of the “surconscience linguistique” typical of Québec, Brea’s version seems to speak to a literary culture attuned to the expressive tensions of Francophone identity. But what defines this “American Francophone Dante”? To answer this, we trace the genesis of the project, which unfolded in two phases: from 2005 to 2012, a pho- netic translation centered on the sound of the original—at times parodic but always reverent; and from 2013 to 2021, a complete rewriting in search of an ideal language that aesthetically legitimizes argot and non-standard registers. Through an analysis of transla- tion drafts and using tools from genetic criticism and linguistic statistics, the study retraces the path of a French speaking globalized Dante.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".