Bibliographic record
Abstract
Cet article cherche à comprendre les dynamiques de pouvoir dans les relations hiérarchiques impliquant des personnages d’étudiant·e·s universitaires et leurs professeur·e·s. Prenant l’exemple du roman québécois, j’examine un échantillon de 11 romans ayant pour personnage principal un·e étudiant·e en lettres, choisis en fonction de la figuration d’au moins un·e universitaire libidineux·euse : La dot de la Mère Missel (2000) de Pierre Tourangeau; Carnets de naufrage (2000) de Guillaume Vigneault; La brèche (2002) de Marie-Sissi Labrèche; Scrapbook (2004) de Nadine Bismuth; Tarquimpol (2007) de Serge Lamothe; Catastrophes (2007) de Pierre Samson; L’impudeur (2008) d’Alain Roy; Enthéos (2008) de Julie Gravel-Richard; L’amour des maîtres (2011) de Mélissa Grégoire; Le corps des femmes est un champ de bataille (2012) de Laurent Chabin; et PsychoZe de Marie-Christine Arbour (2016). Il appert que ces représentations empruntent deux voies : d’une part, l’éros pédagogique peut être déparé de gravité et récupéré dans une logique carnavalesque; d’autre part, il peut servir de catalyseur (positif ou non) dans la quête d’apprentissage des protagonistes. Qu’il s’accompagne d’un arsenal de stéréotypes ou qu’il serve de plaque tournante à une quête de soi aboutie, l’éros pédagogique, analysé en série, dévoile certains mécanismes rendant permutables le sexe et le pouvoir.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".