Bibliographic record
Abstract
Abstract In Renaissance arts, variety was an essential principle, and theorists explained how this aesthetic was to be applied in music. Tinctoris was the first to warn against direct repetition of a contrapuntal combination, while Zarlino and Artusi articulated strict principles for variation. Using Schoenberg’s distinction between the “contrapuntal idea” and the “homophonic idea,” this chapter will survey the types of variation that were used in the presentation of a soggetto and the contrapuntal combination of which it is a part. Then it turns to homorhythmic repertoire, which has not been frequently discussed. In such chordal music, where is the soggetto? In many cases, the bass-line melodically resembles any other thematic melody and is subjected to the same treatment, even though it may never migrate to any upper voice, and while it also provides a foundation for triads. Examples are drawn from works by Rore, Casulana, Lassus, Wert, and Monteverdi. Considering the bass as a theme will help ferry us across the gulf that seems to separate counterpoint from harmony.
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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 | 0.001 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".