Self-Portraits of a Truthful Liar: Satire, Truth-Telling, and Courtliness in Ludovico Ariosto’s <i>Satire</i> and <i>Orlando Furioso</i>
Bibliographic record
Abstract
Composed during the most difficult years of Ludovico Ariosto’s relationship with the Este court, the Satire are known for presenting a picture of their author as a simple, quiet-loving man, and also as a man who can speak only the truth. However, the self-portrait offered by the Satire of the author as a man incapable of lying stands in direct contrast to the depiction presented by St. John in canto 35 of the Orlando Furioso of all writers (and thus, implicitly, of Ariosto) as liars. This article investigates the relationship between such contrasting self-portraits of Ariosto, aiming to overcome the traditional opposition of satire as the mode for honest speech—and for a truthful portrayal of the author’s self—and epic as the mode for courtly flattering. Composée pendant les années les plus difficiles de sa relation avec la cour d’Este, les Satires de l’Arioste sont connues pour la représentation qu’elles donnent de leur auteur comme un homme simple aimant la tranquillité et ne disant jamais rien que la vérité. Toutefois, cette représentation de l’auteur comme un homme incapable de mentir contredit directement la représentation des écrivains (incluant implicitement l’Arioste lui-même comme menteurs, avancée par saint Jean dans le chant 35 de son Orlando Furioso.) Cet article examine donc les relations qu’entretiennent les différents autoportraits qu’offre l’Arioste et cherche à dépasser l’opposition traditionnelle entre la satire comme forme du discours honnête — qui comprend l’autoportrait honnête de l’auteur —, et le discours épique comme mode de flatterie de cour.
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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 | 0.006 | 0.013 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".