Machiavellian Rhetoric: From the Counter-Reformation to Milton
Bibliographic record
Abstract
lady combing ("A Buffer for a Taboo, Combing," 1980).Although Navarrete mentions the sensuality of the poem in a passing reference to ter Horst's article, by concentrating on the Petrarchan nature of the conceit, he fails to emphasize enough the enormous thematic and linguistic changes that have taken place between the Spanish Renaissance and the Baroque.Thus, it is hard to agree with Navarrete when he writes that the "entire poem is based on rather trivial, time-worn comparisons, hyperbolically expanded and compounded by mythological allusions" (p.217), for such a reading makes light of Quevedo's explosive language and marginalizes ter Horst's excellent interpretation.In Quevedo's case, the innovation within his poetry lies partly (a) in the attempted destruction of Petrarchism (Quevedo "is come not to fulfill the Petrarchan tradition but to destroy it," p. 239); (b) in the whole process ofdefami\\a.nza.iion/desautomatizacidn(Pozuelo Yvancos, footnote 32, p. 265, and hence marginalized); and (c) more importantly, in what Blecua has called "el angustioso problemade la vidacomo muerte y de la inexorabilidad del tiempo" (p.265, once again marginalized in a footnote).Finally, although Navarrete assures the reader that Petrarchism in Spain ends with Quevedo (pp.233-240), it would not do to forget either the later works of Calderon or the clearly simplified Petrarchan imitations of Gongora that continue well into the eighteenth century.
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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 | 0.003 | 0.006 |
| 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 | 0.023 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".