How Malleable is the ‘Gold Standard’?: A Case Study in Respect of South Africa’s Access to Information Regime
Bibliographic record
Abstract
This paper examines the difficulties encountered by Biowatch, a South African civil society environmental organisation, in its attempts to obtain access to government information in respect of genetically engineered plants. The elaboration of the case is based on interviews conducted with the Director of Biowatch and the organisation’s legal counsel.Cette communication porte sur les difficultés rencontrées par Biowatch, une organisation environnementale de la société civile sud-africaine, lors de ses tentatives d’obtenir accès aux données gouvernementales relativement aux plantes issues du génie génétique. L’élaboration du cas se base sur des entrevues menées auprès du directeur de Biowatch et le conseiller juridique de l’organisation.
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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 | 0.020 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.027 | 0.018 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".