Byron—In-Between Sade, Lautréamont, and Foucault: Situating the Canon of “Evil” in the Nineteenth Century
Bibliographic record
Abstract
Sade’s evil influence on Lord Byron haunts the margins of Byronic criticism. In this article I resuscitate the marginalized Marquis by tracing Byron’s influence on another son of Sade, the pseudo-Comte de Lautréamont. If Sade’s forever violated heroine Justine forms a hopelessly contradictory representation of Byron’s desire for in-nocence (or non-noxiousness) in the name of himself, his illicit affair with his half-sister Augusta, and his interminably complexrapportto other feminine, homosocial, and homosexual objects of desire, how does this clandestine influence estrange a user-friendly Byron from our comfortable stereotype of the poet as wholly different from thatotheraristocrat? An examination of Sade alongside Lautréamont’s Sadean strain inMaldororreplacesle malat the core of Byron’s life-writing, thereby foregrounding his lordship’s attempt to evade the practical consequences of evil in his own work. Since Sade is also influential on contemporary criticism via poststructuralism orLa Pensée 68,I work through the case of Foucault in order to show how this Sadean order of things is responsible for the tendency to evade confronting the ephemeral or merely literary status of “evil” in the nineteenth century (and beyond).
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.057 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".