Bibliographic record
Abstract
Introduction In recent years there has been an increasing amount of comment about changes in national orchestral performing styles and sonorities during the second half of the twentieth century. It has been argued that in the last few decades traditionally individual sounds and stylistic characteristics of orchestras from specific different countries have been all but eroded and replaced by a more internationally uniform sonority and approach that has gradually but steadily arisen. That is a generalised claim, but nevertheless recordings definitely do illustrate how some very distinctive traits that formerly existed in certain orchestras have now largely disappeared. For instance, fifty years ago there were striking differences between many of the colours, timbres and also styles of phrasing that could be heard in French, Italian, German, Russian, English and American orchestras. And as recently as only a quarter of a century ago this was still very much the case with four of the world's leading orchestras from different parts: the Berlin Philharmonic, Leningrad (now St Petersburg) Philharmonic, London Symphony And New York Philharmonic. Their individually recognisable qualities, such as the Leningrad brass players' stridently strong vibrato and often, though not always, very marcato style (similar in most Russian orchestras) and the darker, richer and more generally blending sounds in Berlin existed to a greater or lesser extent, regardless of who was conducting.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.051 | 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".