Music, gender and the erotic in Italian visual culture of the 16th century: introduction
Bibliographic record
Abstract
In 16th-century Italy, music occupied an ambivalent position in relation to ideals of feminine conduct. On the one hand, it was associated with rational judgement through its long-term theorization within the mathematical quadrivium, founded in Pythagoras and his discovery of harmonic ratios. Both Musica, the personification of the liberal art of music, and the decorous Muses, ancient goddesses of the arts, stood as feminine guarantors of the virtuous nature of this studious pursuit. On the other hand, music was also widely associated with sensation and seduction, bypassing reason thanks to its much-vaunted power to move the passions. This feature in itself had a dual aspect, because music’s moving quality might be harnessed to a pious sensibility within devotional practice—something considered particularly suited to women—or it might equally motivate licentious thoughts among those enjoying love-songs and other characteristically youthful and amorous forms of musical socialization. As a result, numerous conduct books of the period are guarded in their acceptance of women’s musicianship and are sometimes outright hostile to it. Contemporary reactions to different modes of women’s musical participation—singing, playing, dancing, listening—are modulated according to the different bodily operations required for their execution and their potential sexualization.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.013 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".