Bibliographic record
Abstract
Although music-dance making would seem, intuitively, to be part of leisure studies, music and dance very seldom appear beyond the simple form of “activity” and rarely as music-dance making. Many Indigenous peoples conceptualize music-dance making as essential to life, knowledge, and taking care of the earth and cosmos. Seeking insight and wisdom from Indigenous practices and words, this chapter enacts maieutic listening to engage with Indigenous music-dance making that has sustained and nourished Indigenous Kanaka Maoli, Kanaka ‘Ōiwi, and Diné peoples for generations. The aim of the discussion is to gesture to social and political insights that can emerge through dialogue between Indigenous music-dance making and knowledge systems and Western leisure: a dialogue that unprivileges Western leisure. As Indigenous initiatives related to sovereignty, self-determination, and concern for the earth crisscross the world, the presence, power, and survivance of Indigenous music-dance making, as an integral component challenges, enriches, or changes how leisure is imagined and practiced.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".