Bibliographic record
Abstract
Pathbreaking study of a vast and intriguing repertoire: arrangements for keyboard instruments of songs, arias, and other vocal pieces, from the age William Byrd to that of Handel. Keyboard arrangements of vocal music flourished in England between1560 and 1760. Songs without Words , by noted harpsichordist and early-music authority Sandra Mangsen, is the first in-depth study of this topic, uncovering abody of material that is remarkably varied, musically interesting, and indicative of major trends in musical and social life at the time. Mangsen's Songs without Words argues that the pieces upon which these keyboardarrangements were based constituted a shared repertoire, akin to the jazz standards of the twentieth century. In Restoration England, the ballad tradition saw tunes and texts move between oral, manuscript, and printed transmissionand from street to playhouse and back again. During the eighteenth century, printed keyboard arrangements were aimed particularly at female amateur keyboardists and helped opera to become a widely popular genre. Songs without Words considers a wide range of model pieces, including songs of many kinds and arias and other numbers from operas and oratorios. The resulting keyboard versions range from simple and pedagogically oriented to highly virtuosic. Two central issues -- the relationship between an arrangement and its model and the reception and aesthetics of arrangements -- are explored in the framing chapters. The result is a study that will be of great interest toscholars, performers, and anyone who loves the music of the late Renaissance, Baroque, and early Classic eras. Sandra Mangsen is professor emerita of music at the University of Western Ontario.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.027 | 0.006 |
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".