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 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.024 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".