L’univers du talk-show : analyse comparative de <i>Grande écoute</i> de Larry Tremblay et de <i>Small Talk</i> de Carole Fréchette
Bibliographic record
Abstract
Cet article vise à comparer deux pièces québécoises parues presque simultanément et ayant pour toile de fond l’univers du talk-show. Une grande partie de Grande écoute (2015) de Larry Tremblay et de Small Talk (2014) de Carole Fréchette propose en effet une critique des médias, tout en empruntant certains traits à ceux-ci. L’usage du dialogue et le rapport avec le·la spectateur·trice ressortent d’ailleurs transformés au contact du monde de la communication dépeint dans ces comédies dramatiques. On y observe en outre une certaine irruption de l’intermédialité, accompagnée d’une mise en scène singulière de l’intime. Au terme de l’analyse, on peut se demander si la critique de la télévision présentée par les dramaturges se ressemble et dans quelle mesure les deux textes sont susceptibles de participer ou non à la formation démocratique de spectateur·trices ou de lecteur·trices impartiaux·ales au sens où l’entend Martha C. Nussbaum (2015 [1995]).
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.018 | 0.012 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 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".