Les amités particulières: étude de l'homoérotisme latent dans quelques romans arthuriens en vers des XIIe et XIIIe siècles et leurs manuscrits
Bibliographic record
Abstract
Queer studies have generally ignored twelfth and thirteenth-century "canonical" Arthurian verse novels, concentrating on the more explicit chansons de geste and prose romances. However, I argue that these Arthurian novels present both sexual ambiguity and homoeroticism, be they declared or latent. They are expressed by Arthur's knights' "special friendships," and by their constant desire of engaging in hand-to-hand fights. Though the use of war and sickness vocabulary to express love has been observed by scholars, an assiduous reading of Chrétien de Troyes and his successors' novels reveals that they resort to a similar rhetoric in describing a knight's desire both for a lady and for a knightly encounter with an enemy. I study two faces of these novels' homoeroticism, both expressed by a narcissistic fascination: the knights' ambivalent virile friendships and their physical confrontations, corresponding to carnal closeness. To do so I analyze the characters' relationships in five of Chrétien de Troyes' novels, and in a few ludic Arthurian novels. Furthermore, I explore the studied manuscripts' ancient and modern reception, as well as the medieval versions available to modern translators. This confirms my reading of these novels, since medieval scribes and illustrators appear to have shared it.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.013 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".