‘If I speak English, does it make me less black anyway?’‘Race’ and English in South African desegregated schools
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
This article focuses on the role language plays in constructing youth identities that are in flux in desegregated suburban schools in South Africa. Interview and participant observation data were collected in three racially mixed schools in Johannesburg. My analysis of the data is set against a discussion of the problematic concept of race and of the historical classification of South African English according to ‘race’ as well as the position of English in South Africa at present. The article presents an analysis of the ways in which learners recognize and characterize the different kinds of English used around them, attaching prestige to varieties perceived as white. The tension between learners' valuing of what is perceived as white English and their labelling of black learners who ‘speak like a white person’ or who no longer speak African languages (either through lack of proficiency or choice) as ‘coconuts’ is explored. The article attempts to open up a debate on race and language use among youth in South Africa, and on race and varieties of English in particular.
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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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