Raciolinguistics and the aesthetic labourer
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
Select studies on aesthetic labour explore how race becomes a component in ‘looking good’ for customers. However, there is little mention of how race is also salient in ‘sounding right’. This article addresses this issue by exploring the impact of race on the vocal demands placed on aesthetic labourers. Using raciolinguistics, a field that investigates the interconnections between language and race, the article specifically notes how two sites of language-focused aesthetic labour, English language teaching and Indian call centres, reinforce conceptions of sounding right that privilege Whiteness. A review of the literature from these sites highlights how looking good and sounding right constitute one another. Indeed, while a White body in English language teaching signifies nativeness/clarity in English, Indian call centre agents make themselves look better in the minds of western callers by ‘whitening’ their voices. These examples act as a call to simultaneously examine the racialized body and voice in future aesthetic labour research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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