Between Reality and Symbol: Fierce Dogs and Ferocious Wolves in the <i>Decameron</i>
Bibliographic record
Abstract
Non-human animals have a long history of being utilized to understand human nature, and both wild and domestic canines have been particularly intertwined with humanity since ancient times. This article examines the representation of animals, and specifically of dogs and wolves, in Boccaccio’s Decameron. The analysis posits Boccaccio’s canine portrayals as multifaceted in nature, serving as tools for the interpretation of human behavior and also reflective of shifting views on the purpose of animal portrayals in literature. The article explores these ideas, in part, through interpretation of Boccaccio’s canines in comparison to those in other sources, with an emphasis on Dante’s Divine Comedy. Given the fact that the Commedia hosts a proliferation of allegorical beasts whereas the Decameron focuses on portrayals of commonplace, living animals, one might expect significant differences in the texts’ treatment of dogs and wolves. Yet, although differences exist, a study of both texts reveals a common outlook on the canine family; and the Decameron’s treatment of dogs and wolves not only reflects that of the Commedia, but also the confluence of wolves and dogs with one another. The article’s primary subjects of discussion from the Decameron are the widely-read story of Nastagio degli Onesti’s otherworldly vision in V.8, and the lesser-known novella IX.7, featuring Talano d’Imole, his wife Margherita, and a brutal wolf attack. In addition to examining literary sources, the article touches upon hierarchical views of wild and domestic canines in daily life from the period for its analysis.
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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 | 0.001 |
| Science and technology studies | 0.009 | 0.024 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".