“Seeing Law in Terms of Music” A Short Essay on Affinities between Music and Law
Bibliographic record
Abstract
It is often believed that law and the arts have very little in common, since law is perceived as a rather formalistic and inaccessible subject incapable of eliciting emotions in the same way as the arts. This article, however, aspires to offer a different picture : by exploring music in its interconnectedness with law, it condenses the main arguments discussed by literature to ultimately show that law and music may reveal, after all, surprising affinities, so that some thought-provoking parallels between them can be made. Similarly, the paper strives to find points of connection between law and music in order to show the profound resiliency of law as an academic discipline. Finally, the paper advances the idea that the unbridgeable distance between the two disciplines exists (partially) in appearance only and that, in spite of its allegedly technical nature, law is a very flexible field of knowledge whose intellectual structure can influence and inform other creative processes.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.015 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".