West African Drumming and Dance in North American Universities
Bibliographic record
Abstract
More than twenty universities and twenty other colleges in North America (USA and Canada) offer performance courses on West African ethnic dance drumming. Since its inception in 1964 at both UCLA and Columbia, West African drumming and dance has gradually developed into a vibrant campus subculture in North America. The dances most practiced in the American academy come from the ethnic groups Ewe, Akan, Ga, Dagbamba, Mande, and Wolof, thereby privileging dances mostly from Ghana, Togo, Benin, Senegal, Mali, Guinea, and Burkina Faso. This strong presence of a world music ensemble in the diaspora has captured and engaged the interest of scholars, musicians, dancers, and audiences. In the first-ever ethnographic study of West African drumming and dance in North American universities the author documents and acknowledges ethnomusicologists, ensemble directors, students, administrators, and academic institutions for their key roles in the histories of their respective ensembles. Dor collates and shares perspectives including debates on pedagogical approaches that may be instructive as models for both current and future ensemble directors and reveals the multiple impacts that participation in an ensemble or class offers students. He also examines the interplay among historically situated structures and systems, discourse, and practice, and explores the multiple meanings that individuals and various groups of people construct from this campus activity. The study will be of value to students, directors, and scholars as an ethnographic study and as a text for teaching relevant courses in African music, African studies, ethnomusicology/world music, African diaspora studies, and other related disciplines.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.020 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.004 |
| 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".