In the Image of Bach: The Unaccompanied Violin Sonatas of Friedrich Wilhelm Rust
Bibliographic record
Abstract
In this dissertation I examine unaccompanied violin music by the German composer Friedrich Wilhelm Rust (1739–1796), seeking to extract and contextualize information about his approaches to violin performance practices and pedagogy. Rust had very close biographical and geographic connections to the Bach family, and I argue that his two unaccompanied violin Sonatas of 1795 are structurally modelled upon J.S. Bach’s iconic 1720 Sei Solo for unaccompanied violin; I also demonstrate that Rust’s Sonatas were written with strong pedagogical intent. Collectively, these features position Rust and his works as a rare window into performance practices in circles directly tied to the Bach family. My research in these areas was conducted through careful biographical, archival, and performance study of works by Rust and his contemporaries and provides historical evidence for approaches to 18th century performance practice which have not yet been widely utilized within the historically informed performance movement. Chapters of the dissertation concern Rust’s biography, the state of unaccompanied violin music in the long 18th century, Rust’s numerous unusual works for unaccompanied violin, and a thorough examination of the performance practices made evident in original manuscripts of Rust’s Sonatas. The final result is not a performance guide to Rust’s Sonatas or Bach’s Sei Solo, but rather an invitation to reconsider current approaches to historically informed performance of the 18th 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 | 0.001 | 0.002 |
| 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 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".