Burur & Interactive Wearable Sound Art: Feeling the Unspoken Excess of Somali Diasporic Affect
Bibliographic record
Abstract
Those in the Somali and larger Black Diaspora in Canada have learned to navigate this liminal space where we negotiate our cultural identity and expression to fit into white hegemonic society. This practice is known as code switching. This ability to adapt and fit into various settings and situations while still holding on to your culture is often seen as a superpower in the Black Diaspora, but it is also a heavy burden. Code switching is the need to conform and express oneself in a palatable way in colonialist societies. In my research I explore how concepts like the Technovocalic Body, Black technopoetics, sonic substance, and Toloobid might create an alternative way of self expression that allow for those in the Black Diasporic to speak and literally feel their ineffable thoughts and emotions while reaffirming their cultural identity. This project utilizes research-creation to create a wearable interactive sound art piece, the Burur Device, that allows a person to haptically engage with affectively charged sonic media and respond to it by distorting it and imbuing it with their own feelings. The Burur Device was created by attending Somali cultural events and engaging with the sound recordings of these to recreate a sonic space to inhabit, feel and distort. The immersions and immediacy of interactive haptic sound capabilities of the Burur Device offer a way for those in the Black Diaspora to express, materialize and embody the ineffable pressures of code switching that alludes language (for now).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".