Érik Canuel, transcréateur : Le Survenant (2005) et autres films
Bibliographic record
Abstract
Entretien accordé à Marie Pascal, Université Dalhousie Après avoir accompagné son père sur des tournages depuis son plus jeune âge, Érik Canuel a commencé la réalisation à vingt ans. Il a adapté plusieurs textes littéraires québécois (des romans avec Le Survenant (2005), Cadavres (2009), Lac Mystère (2013) ; une autobiographie avec Le dernier tunnel (2004) et une pièce de théâtre avec Barrymore (2011). Son film emblématique est Bon Cop, Bad Cop (2006) avec l’acteur Patrick Huard. Le réalisateur est également connu pour de nombreux clips de musique et des émissions TV. Collectionneur de bandes-dessinées et féru de musique, Canuel a pour objectif de mettre en valeur les arts les uns grâce aux autres afin de faire résonner son public, comme si chacun d’entre nous était un instrument de musique. Dans cet entretien, il conte sa réflexion sur ses adaptations cinématographiques, notamment Le Survenant.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".