Bibliographic record
Abstract
The article revisits Inferno 26-27 from the perspective of the medieval pastoral debate on peccata linguae and focuses on the controversial phrase consiglio frodolente (Inf. 27.116). I begin my analysis by examining the notion of pravum consilium ‘evil counsel’ in two tracts on verbal sins: William Peraldus’ “De peccato linguae” (c. 1236) and Domenico Cavalca’s Il Pungilingua (1330-1342). In the second part of my essay, I analyze the figure of Ulysses in relationship to that of Guido da Montefeltro and argue that consiglio frodolente is not a misnomer for the sin of bolgia eight, as some commentators have contended. In the above-mentioned ethical tracts, the most salient feature of pravum consilium is its connection with fraud. In coining the phrase consiglio frodolente, Dante highlights this connection and renders this verbal sin perfectly consonant with the system of Malebolge. Cantos 26 and 27 of the Inferno mark a significant stage in the history of pravum consilium as a moral notion that situates itself at the intersection of speech, ethics, and politics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".