It's all in your head: a defence of idealism in the ontology of musical works
Bibliographic record
Abstract
The view that musical works are mental entities, known as "idealism," is massively rejected by ontologists of music. Their central argument is that key features of mental entities are inconsistent with those of musical works. Specifically, mental entities are usually agreed to be subjective and particular, whereas musical works are claimed to be objective (at least in the sense that they can be heard by many people at once) and generic (at least in the sense that they can be the object of multiple performances, each of which may be slightly different than the others). My goal in this thesis is to show that certain collections of mental entities can be said to be objective and generic in a way that is consistent with their being musical works, and thus that the objections typically used to dismiss idealism actually fail. The thesis is articulated as follows. After introducing basic ontological issues raised by musical works and investigating related methodological issues, I examine the main objections that have been raised against idealist accounts of musical works. The force of these objections is found to rest with the assumption, closely connected to idealism but not essential to it, that musical works consist of "inner hearings." I propose to replace this assumption with some of the tenets of the very influential view that musical works are types and their interpretations tokens. These tenets are adapted to an idealist framework articulated around empirical findings in musical cognition. The result is the notion of "psychological types," which are argued to be collections of mental entities that are both objective and generic in a sense suitable for their being musical 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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.065 |
| Scholarly communication | 0.009 | 0.016 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".