Bibliographic record
Abstract
In his Geographies, Strabo notes that the ancient Iberian city of Tartessus is associated with Hades.1 Strabo is only one of many classical authorities, dating back to Homer, who connects the mythological god of the underworld to the Iberian Peninsula. The correlation is likely due to the prosperous mines which were located in the vicinity of the Iberian Peninsula.2 Mythographers reinforced the connection between Pluto and wealth etymologically by drawing attention to the similarities between the names of Pluto and Plutus, the Greek god of riches.3 In early modern literature, Pluto’s association with wealth and riches is well attested.4 Less obvious (to me) is any literary association with Iberia. By comparison, Proserpina—Pluto’s consort—has a terrestrial connection to Sicily, since this is where she resided at the time of her abduction.5 Proserpina’s geographical association with Sicily is also well attested in late medieval and early modern literature.6 With respect to Matteo Bandello’s 22nd Novella, at least one critical study has detected echoes of the myth of Proserpina in the ritual death and rebirth of Fenicia, and the Novella’s Sicilian locale.7 To my knowledge, though, no one has evaluated the extent to which the character of Timbreo, who originates from a wealthy house in Cardona, operates analogously in a Plutonian capacity of moral violator and reconciled husband. Although it is likely that Bandello was inspired by historical events for his use of the Sicilian setting, I would be curious to know if there is any evidence whatsoever to support a conjecture of an Iberian Pluto being echoed in the character of Timbreo.8 For NQ readers with an interest in the reception of classical mythology in late medieval or early modern literature, do you recall any other corroborating literary echoes of an Iberian Pluto? I suspect that Pluto’s more prominent association with the geography of the underworld and material riches left little conceptual space for the development of an Iberian sub-identity. However, if readers do know of any literary echoes, I would be interested in learning about them. Even the existence of minor evidence might motivate us to re-evaluate the important literary texts which owe a meaningful debt to Bandello, such as Shakespeare’s Much Ado About Nothing and The Winter’s Tale.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".