Perception of Musical Similarity Among Contemporary Thematic Materials in Two Instrumentations
Bibliographic record
Abstract
Free classification was used to explore similarity relations in contemporary musical materials. Thirty-four subsections from the five themes of The Angel of Death by Roger Reynolds were composed identically for piano (Expt. 1) and chamber orchestra (Expt. 2) in terms of pitch, rhythm, and dynamics. Listeners were asked to group together those judged to be musically similar and to describe the similarities between the subsections in each group. Listeners based their classifications on surface similarities related to tempo, rhythmic and melodic texture, pitch register, melodic contour, and articulation. They were to some extent also based on similarity of the mood evoked by the excerpts. This latter factor was more prominent in the verbalizations for the orchestral version. Instrumentation, timbre, and type of timbral change (smooth, disjunctive) also affected classifications in the orchestral version. Perceptual relations among thematic materials within the piece and the interaction of form-bearing dimensions in musical similarity perception are discussed.
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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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".