Bibliographic record
Abstract
Venanzio Rauzzini (1746-1810) enjoyed a significant and varied musical career in Britain that lasted from 1774 until his death.During this time, he variously sang in Italian opera performances in London, composed instrumental and vocal music, directed a concert series in Bath for thirty years, and was one of the most respected singing teachers in Britain.As a foreigner, a Catholic and a castrato, Rauzzini was someone who was "other," both socially and physically.Unlike the visiting operatic castrati who preceded him, Rauzzini was the first castrato singer to make Britain his permanent home, rather than returning to the Continent after his performing days were over. 1 That he would achieve a position of cultural leadership in Britain was both unprecedented and unexpected.In the process, he became a target of distrust and suspicion by those who could not envision a castrato in a leadership role.The implications of Rauzzini's varied career are considerable, and reveal how the changing social and political demographics of Britain affected not only how concert music was perceived by its audience, but also what music should be performed and by whom.This paper explores some of the resulting tensions experienced by Rauzzini during his British career, especially during the late years of
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".