Bibliographic record
Abstract
This article aims to identify the criteria by which the Karakalpak bards of Central Asia evaluate the performance of their epics. To do so, Frederic Leotar analysed the vernacular terminology used in listening situations. First, the author played archive recordings of the most esteemed masters from the 1960s, but these did not give rise to detailed verbalization. Faced with this methodological obstacle, the researcher then decided to propose pieces played by novices, and specifically the pop rendition of part of a traditional epic. A number of terms and expressions referring to several key criteria of Karakalpak musical culture emerged from the commentaries first collected from a professional bard (G’ayrat O’temuratov), then confirmed by others. Paradoxically, the criteria, as they were felt and expressed by advocates of traditional Karakalpak epics, came out in a much more explicit way in response to the pop version than to the versions of reference. In this instance, the discussion around the modern version allowed for the revelation of aesthetic markers used by the most accomplished bards, specifically because this version was missing certain key elements of the traditional versions, the latter generally not eliciting detailed comments.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".