Mapping Music: Cluster Analysis Of Song-Type Frequencies Within And Between Cultures
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Understanding cross-cultural patterns of musical diversity requires some method of visualizing these patterns using maps. The traditional methods of cross-cultural comparison have been criticized for ignoring the rich diversity of musical styles that exists within each culture. We present a compromise solution in which we map the relative frequencies of different "cantogroups" (stylistic song-types) both within and between cultures. Applying this method to 259 traditional group songs from twelve indigenous peoples of Taiwan, we identified five major cantogroups, the frequencies of which varied across the twelve groups. From this information, we were able to create musical maps of Taiwan. (This article refers to a supplementary speadsheet that can be found at http://neuroarts.org/pdf/Savage_Brown_2014_Supplement.xls)
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it