Bibliographic record
Abstract
The HIV/AIDS epidemic in South Africa has been well documented. There have been books that tried to understand why the epidemic is so serious and what has driven the response, in particular the baffling politics of AIDS. These included the classic ethnography by Campbell (2003), Fourie (2006), Nattrass (2007) and Lawson (2008). Biographical accounts included Cameron (2005) and McGregor (2006). The epidemic makes an appearance in South African fiction, from books specifically centred on it (Steyn, 2007); to those where it is in the background (Morojele, 2006); to mentions in detective fiction (Meyer, 1999). There have been moving exhibitions, both photographic and in other media, documenting the scale and effect of HIV/AIDS. Most of these books are written by white South Africans. The voice of the people is generally not heard, although the perceptive book by Nolen (2007) (a white Canadian journalist living in Johannesburg) goes some way to redress this.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".