Gronde vir die weiering van toegang tot inligting soos van toepassing op openbare instellings (deel II)
Bibliographic record
Abstract
The right of access to information as contained in section 32 of the Constitution of the Republic of South Africa, is not an absolute right. It has to be limited in order to protect sensitive material of which the disclosure may cause damage to individual or public interests. In light of this, the Promotion of Access to Information Act 2 of 2000 (PAIA) contains a number of legitimate grounds for the refusal of information. Part I of this article provided an explanation of the structure of the grounds for refusal, looked at the principles relevant to their correct interpretation and continued with an analysis of the first six grounds as contained in the PAIA. In part II, the remainder of the grounds for refusal that are applicable to public institutions, are examined (sections 40 to 46). These grounds, amongst others, relate to records concerning the defence, security, international relations and economic and financial welfare of the Republic, records that reveal research information of a third party or a public institution and records concerning the operations of public institutions. As was the case in part I, the grounds are analysed with reference to corresponding provisions of the American Freedom of Information Act, the Canadian Access to Information Act, the New Zealand Official Information Act and the Australian Freedom of Information Act.
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.095 | 0.025 |
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".