<i>Kutanga</i>, <i>Mujimbu</i>, and the Tacit Orchestration of Events Among the Luvale of Zambia
Bibliographic record
Abstract
Orchestration is an established topic in various music disciplines yet is a rare focus in ethnomusicology. This paper offers a modest remedy by asserting that culturally expected timbral interactions are orchestration. McAdams et al. (2022) define orchestration as the selective combination and juxtaposition of instruments to achieve sonic goals. With this case study, I reorient orchestration towards cultural goals. I also assert that any sonic event can be orchestrated (not just music). Furthermore, I argue that any event participant can be an agent of orchestration. Among Luvale (and related) communities in Zambia, there exist similar traditions of recounting one's recent journey through an oral briefing: kutanga and mujimbu. Although related, these events have different social functions, participants, and orchestrations. Kutanga is a dance prelude for a specific group of makishi (manifest ancestral spirits) or boy initiates and involves the alternation between vocalizer and drum. Mujimbu, featuring loosely coordinated clapping and alternating speakers, is enacted when a different set of makishi or men arrive somewhere. Both events involve expectations of vocal, clap, and drum timbres participants should employ. Whether these timbral decisions are deliberate or tacit (Arom 1981; Brinner 1995; Polanyi 1966), I interpret them as results of encultured behavior (Eidsheim 2019). In this paper I contend that orchestration is culturally informed, helps define and differentiate events, and links makishi to their living counterparts. To accomplish this, I delineate events in terms of orchestration, performers, and social function (Arom et al., 2019; Fürniss 2006, Nzewi 2008), analyze interviews, and culturally contextualize timbre. Although Kubik has conducted extensive research on kutanga (1971, 1974, 1977, 1994, 2008, 2010), his findings do not address orchestration or its ability to connect the ancestral to the living. An ethnomusicological approach to these events offers timbre studies a window into the cultural components and ramifications of orchestration.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".