Bibliographic record
Abstract
In the article, the author reflects on the problem of musical identity and notes that the structure of writing, like any writing, excludes any idea of a written text as unchangeable and eternal, because the signification, representation and replacement of one meaning or context by another occur in it endlessly and without closure. By analogy with the "textual strategies" characteristic of Jacques Derrida's approach to literary theory, criticism, and philosophy of language, the article proposes to consider the problem of musical identity. The author rightly speaks about the differences in interpretation and performance, which results in an immeasurable richness of colors of a musical work, its refusal to be exhausted, and its differences from other works. Consequently, performance ethics should no longer focus solely on defining and implementing compositional intent, for this is not the only origin of what is written. A musical work is a creative process of the composer, embodied in a live sound through interpretation by performers, which must take into account what goes beyond the intention and context, the meaning of which cannot be discovered by referring to the original and lost context, but must be created in the present, which is always another present of the inscription.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.018 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".