Paralinguistic Ramification of Language Performance in Islamic Ritual
Bibliographic record
Abstract
Across time and space, Islamic ritual practices maintain certain fixed features while adapting to local environments, thereby developing a branching or ramified structure—though political, economic, ideological, or technological factors may cause certain local forms to globalize as well. Such ramification offers a means of interpreting the past as well as a window into religious meaning and the ritual process itself. How does such adaptation take place, what drives it, what is its social-spiritual meaning and impact, what can such a ramified variety across history and place tell us, and where does the essence of such ritual lie? In this paper I argue that just as Islam centers on language, Islamic ritual practice centers on “language performance”, whose variegated forms and meanings are intertextually linked via common roots in sacred originary texts. Islamic language performance should not be conceived as lying on a continuum from “speech” to “song”—a distinction which obscures rather than illuminates—but rather as an integral category embracing an enormous range (from sermons to chants) of forms, whose critical internal distinction is rather linguistic/paralinguistic, or reference/expression. Within this domain, it is primarily paralinguistic features that adapt, shaped through feedback processes. By contrast, the scope of linguistic ramification is constrained. This paper proceeds to explore the significance of language performance in Islam, both in theory and in practice—through the presentation of contrastive examples in three primary domains of language performance: the call to prayer (adhan), Qur’anic recitation (tilawa), and congregational supplication (du`a’). These examples shed light on the distribution and meaning of diverse Islamic ritual practices, on their interconnections, and on the processes by which they emerge.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.021 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 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".