Bibliographic record
Abstract
One could almost feel the earth tremble from the cheering when newly installed President Kgalema Motlanthe announced the removal of Dr Manto Tshabalala-Msimang from the health portfolio in the new cabinet. The nightmare was finally over. South Africa was rid of a health minister, once described as 'a drunk and a thief', whose bizarre views on HIV and AIDS had made her the laughing stock of the international community and an object of intense embarrassment here at home. In one of her more spectacular acts of buffoonery, she had the official South African exhibition stall at the 2006 International AIDS Conference in Toronto display garlic, lemon and beetroot as South Africa's remedies of choice in the management of HIV and AIDS, prompting a group of more than 60 international HIV experts, including Robert Gallo, co-discoverer of the HI virus, to write to President Thabo Mbeki to echo the numerous and repeated calls here at home for her to be fired. The calls were stubbornly ignored by President Mbeki.
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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 | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.011 | 0.012 |
| Insufficient payload (model declined to judge) | 0.052 | 0.036 |
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".