Symphonies in the stacks : how libraries can aid in classical music’s revitalization
Bibliographic record
Abstract
Classical music as an art form is as vibrant and engaging as ever, but it is steadily losing the ability to connect to the greater community. It is an industry like any other, and must keep itself relevant in order to remain afloat. Libraries have faced many of same challenges, but unlike the classical music world, they have had far more success in adapting to new technologies and adopting new models for operation. Classical music must learn to do the same, and collaboration with libraries is a fundamental first step in accomplishing this. This paper examines some of the ways collaboration is already taking place, and suggests ways it can further aid audience revitalization through providing access for the library community.
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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 | 0.012 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.015 | 0.006 |
| Scholarly communication | 0.026 | 0.039 |
| Open science | 0.004 | 0.031 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.040 | 0.015 |
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".