Gronde vir die weiering van toegang tot inligting soos van toepassing op openbare instellings (deel I)
Bibliographic record
Abstract
The Promotion of Access to Information Act 2 of 2000 (PAIA), like all other legislation governing the right of access to information, provides for a number of legitimate grounds for the refusal of information. This article explores these grounds but only as far as they are applicable to public institutions. Part one of the article starts out by explaining the structure of the grounds for refusal and the principles which are crucial to the correct interpretation of the grounds. It then goes on to analyse the first six grounds as contained in the PAIA (grounds seven to thirteen are covered in part II). In order to provide a constructive analysis of the specific grounds, corresponding provisions of the American Freedom of Information A c t, the Canadian Access to Information A c t, the New Zealand Official Information Act and the Australian Freedom of Information Act are drawn upon. The wording of the statutory exemptions contained in the legislation of the above-mentioned countries, along with the interpretation given by appeal and review mechanisms, were taken into consideration not only to make proposals regarding the South African situation, but also to enhance understanding of the grounds for refusal as contained in the PAIA.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.075 | 0.019 |
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".