Farewell to the Rainbow Nation? : a conversation between Oscar Hemer, Bronwyn Law-Viljoen, Masande Ntshanga and Ivan Vladislavic
Bibliographic record
Abstract
More than a quarter of a century since Nelson Mandela became the country’s first democratically elected president, the racial categories of apartheid live on in South Africa. The proud vision of the “Rainbow Nation” is now being challenged by various forms of populism, with racial thinking as the common denominator. How can one advocate for non-racism and cosmopolitanism—in South Africa and the world—without being perceived as a defender of the privileges of the white minority? Oscar Hemer, Professor of the Arts at Malmö University, considers these questions in discussion with South African author colleagues Masande Ntshanga, Ivan Vladislavić and Bronwyn Law-Viljoen.
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.
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 | 0.014 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.021 | 0.013 |
| Scholarly communication | 0.013 | 0.018 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.010 | 0.022 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".