Against ethnomusicology: Language performance and the social impact of ritual performance in Islam
Bibliographic record
Abstract
Abstract This article argues that ‘music’ is unsatisfactory to reference sounds of ritual performance in Islam, not only because the term has been controversial for Muslims, but especially due to its unremovable pre-existing semantic load centred on non-referential aesthetic sound, resulting in drawing of arbitrary boundaries, incompatibility with local ontologies and under-emphasis on the referential language lying at the core of nearly all Islamic ritual. From the standpoint of the human sciences, this study is interested in the understanding of such rituals as combining metaphysical and social impact. Use of ‘music’ tends to distort and even preclude holistic ritual analysis capable of producing such understanding. As a result, ethnomusicology is misdirected. Theoretically and methodologically, this article develops an alternative concept, ‘language performance’ (LP), including four aspects – syntactic, semantic, sonic and pragmatic – especially designed for Islamic ritual performance. Applying a linguistic theory of communication developed by Jakobson, it shows how LP can be developed as a comprehensive, descriptive framework for comparative ritual analysis, akin to Lomax’s global Cantometrics, but avoiding its flaws through a more flexible design and modest scope, enabling systematic, comparative investigations of performance in Islamic ritual. The article closes with an example of such analysis centred on Sufi rituals in contemporary Egypt.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.049 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| 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".