Bibliographic record
Abstract
Bernstein was a prolific recording artist, and this chapter considers his vast recorded legacy, from his earliest recordings made in the 1940s to later ventures, including several important opera sets as well as a large swathe of orchestral repertoire, with the symphonies of some composers (notably Beethoven, Schumann, and Mahler) recorded more than once. As well as mainstream European repertoire, Bernstein never lost his enthusiasm for recording music by American composers, including outstanding discs of Copland, Foss, Harris and Ives. While Bernstein was usually pleased with the results of his sessions – whether in the studio or recorded live in concert – he also felt the need at times to return to composing. These creative phases were intermittent (Bernstein was usually at his happiest when working with other musicians), but the consequence was a healthy output of new work, most of which Bernstein himself subsequently recorded, including two cycles of his symphonies and recordings of his major stage works.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.170 | 0.048 |
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".