Bibliographic record
Abstract
In traditional Indigenous southern plains culture, a young man could not talk to a young woman alone when they were not yet married. Instead, he would play his flute at the edge of the encampment in the evenings, and each young man had his own love song. In southern plains flute origin stories, power is attributed to good music. If a flute song achieves its intended goal of convincing the young woman to marry the flute player, one can assume the song would be considered “good.” But what criteria distinguish good from bad? Which elements typify a “good” flute song? What about the flute itself? Which features epitomize the quintessential flute? Another set of possible criteria in determining that quality is information about the flute player. In her chapter, “Culture and Aesthetics,” ethnomusicologist Marica Herndon (1980) observes the community-centered perspective of Indigenous North America. Our last set of criteria involves an assessment of the moral character of the flute player regarding service to their tribal community. This talk discusses the “good music” of two master Indigenous southern plains flute players—Belo Cozad (1864-1950) (Kiowa) and Doc Tate Nevaquaya (1932-1996) (Comanche).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.012 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".