Bibliographic record
Abstract
South Africa's Protection of Constitutional Democracy against Terrorist and Related Activities Act 33 of 2004 is compared with Canada's Anti-Terrorism Act, 2001. The processes that led to the enactment of the two laws and the packaging and preambles of both laws are examined. The definitions of terrorist activities in both laws are compared, as are the fault elements in various offences related to terrorism. South Africa's extensive use of negligence or lIgculpal/Ig liability is contrasted with Canada's use of subjective fault and various constitutional arguments concerning the necessity for subjective fault for terrorism are examined. South Africa's duty to report offence is compared with the comparable Canadian offence, and investigative hearings and powers in terrorism cases in both countries are examined with an emphasis on prior judicial authorization and a presumption of publicity. The process for the listing of terrorist groups in both countries is also compared. Conclusions are drawn that, while more limited in scope than the Canadian law, South Africa's new anti-terrorism law has a broader defi nition of terrorism, lower fault levels, a broader duty to report offence and less restrained investigative powers.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".