Gender Performativity in Chaucer’s Troilus and Criseyde and Shakespeare’s Troilus and Cressida
Bibliographic record
Abstract
Mon mémoire s’intéresse à la performance des genres dans l’histoire de Troïlus et Criseyde telle que présentée dans Troilus and Criseyde de Geoffrey Chaucer et Troilus and Cressida de William Shakespeare. En s’appuyant sur la théorie de Judith Butler, mon analyse explore d’abord l’influence de l’amour courtois sur les attentes sociales dépeintes dans les deux versions du récit. Les règles d’Andreas Capellanus servent de base pour comprendre les restrictions imposées par l’amour courtois et leur effet sur l’histoire d’amour de Troïlus et Criseyde. Ensuite, les thèmes de l’amour et de la guerre aident à définir la performance de la masculinité de Troïlus et Diomede, tout en permettant de comparer leur relation avec Criseyde. Finalement, la commodification du corps de la femme est présentée comme une conséquence inévitable de la performance de la fémininité telle qu’encouragée par la société. L’alternance entre les textes de Chaucer et de Shakespeare montre que la performance des genres a très peu évolué entre le Moyen-Âge et la Renaissance et suggère ultimement que certaines attentes sont toujours les mêmes dans la société occidentale contemporaine.
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.028 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".