The Pearl of Tuva: Authenticity and Tuvan Khorekteer (Throat Singing)
Bibliographic record
Abstract
Abstract: The Russian Republic of Tuva is home to the solo multiphonic singing styles encompassed under the umbrella terms khorekteer and khoomei. This paper explores the conceptual complexities of authenticity pertaining to Tuvan throat singing. The author reveals ethnicity and race as primary authenticity markers as expressed by indigenous performers of Tuvan music. This paper also examines the events surrounding the 2002 Dembildei International Throat Singing Competition held in Tuva’s capital city Kyzyl. Concerns of authenticity as expressed by the panel of judges for Dembildei 2002 are presented alongside some other political, social, and economic forces that resonate around this event. I recall an advertising campaign initiated by the popular clothing and accessory giant, GAP in 1994. Rolling Stone was one of many magazines to feature a full-page spread of a contemplative Miles Davis seated somewhat awkwardly in a metal studio chair and dressed in khaki trousers. The photograph was taken nearly forty years before the GAP’s advertising crusade for the revival of plain khaki pants. A series of memorable GAP television advertisements that hit the airwaves in 1999 always concluded with the perfunctory catch phrase ‘This is original. ” One of the more short-lived commercials featured trumpeter and co composer of The Little Spanish Flea, Herb Alpert. Alpert wandered the stark white backdrop of
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".