Land without Nightingales : music in the making of German-America
Bibliographic record
Abstract
Despite the laments of some nineteenth-century German immigrants that America was a bereft of poetry and song, a land without nightingales, the history of German American music is a rich one. This book explores the wide variety of forms of musical expression among German-speaking immigrants to America and their descendants from the eighteenth century to the present. Topics range from Moravian music in colonial America to musical life among twenty-first century Canadian Hutterites, from polka music to German singing societies, from Lutheran hymns to the songs of German-speaking Catholic and Jewish immigrants, and from the songs of German-speaking Swiss settlers to the music of immigrants from the Burgenland region of Austria. Underlying these diverse contributions is a common theme the constant interplay between the German and American sides of the hyphen of German-American to be found in all these musical styles. A companion CD includes musical selections that complement and expand upon this theme. The contributors historians, musicologists, folklorists, and scholars of German studies include Philip V. Bohlman, Alan R. Burdette, Kathleen Neils Conzen, Otto Holzapfel, James P. Leary, Laurence Libin, Rudolf Pietsch, A. Gregg Roeber, Leo Schelbert, and Helmut Wulz.
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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 | 0.000 |
| 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 | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".