Rire pour dénoncer : les enjeux féministes contemporains dans l’humour de la relève québécoise et acadienne
Bibliographic record
Abstract
S’appuyant sur les théories féministes et queers (Wittig, 2001; Butler, 2005; De Lauretis, 2007) reconnaissant le caractère construit et la performativité du genre dans les représentations et les discours (De Lauretis, 2007) et le quotidien (Butler, 2005) ainsi que sur les théories de l’humour dont ceux sur l’ironie (Jankélévitch, 2011 [1964]) et sur l’humour des femmes (Joubert, 2002; Melchior-Bonnet, 2021), le présent mémoire porte sur les manières dont les humoristes québécois·es et acadien·nes de la relève font du système hétéronormatif l’objet privilégié de leur répertoire. L’objectif principal vise à identifier les cibles récurrentes de leurs blagues ainsi que les principaux procédés discursifs et humoristiques mobilisés. L’objectif secondaire est de détecter les différences entre les positions des humoristes féminines et masculins face aux mêmes enjeux, dans un corpus composé de numéros de Coco Belliveau, Suzie Bouchard, Charles Pellerin et Colin Boudrias.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.015 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".