Bibliographic record
Abstract
Balinese composer Dewa Alit (b. 1973) splits his time between home and abroad, absorbing many kinds of music. His latest gamelan work (2016) is Ngejuk Memedi , from the Balinese ngejuk , to chase, and memedi , a feared phantom of the Balinese unseen world that takes human form. It animates his evolving desire for a “broader conception of what gamelan is, one based on its relationship to other cultures” (Alit in Tenzer 2011, 134), while submitting to the phantom-like elusiveness of the goal. In analyzing part of Ngejuk Memedi , this article argues for an emergent musical supra-culturalism embedded in innovative rhythmic practices. In Alit’s case, three strata of metrically dissonant parts are superposed in a continually changing relationship. His procedures are suggestive of those of other contemporary musicians from around the globe, whose kinship with Alit comes into focus once one delimits the intellectual and aesthetic desiderata they have challenged themselves to explore. Often notated by composers but transmitted and performed orally, such music is highly conceptual but deeply embodied in felt groove. Its signature element is the juxtaposition or layering of complex, asymmetrical periodicities that are rare or unknown in source traditions, but trace to ideas circulating from African, Indian, Western and other art musics that have become common currency. In these intersecting senses, they comprise a new phenomenon.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.036 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".