'Stacking the odds against the accused' : appraising the curial attitude towards amici participation in criminal matters
Bibliographic record
Abstract
The law governing amicus curiae participation in criminal matters was recently laid down in S v Basson: Ex Parte Institute for Security Studies which was followed by S v Zuma. It essentially requires the court to be cautious in not allowing amicus curiae participation where this will stack the odds against the accused. Looking at the history, primary role and utility of amici curiae and how the courts in Canada and the US treat their participation particularly in criminal matters, it is suggested that South African courts should not hastily disallow their participation in criminal matters. A court faced with an application by an aspirant amicus curiae must embark on a three-stage enquiry. The first and obvious question is whether amicus curiae will aid it not to err. Secondly, will its participation compromise the parties' fair trial rights? And lastly, are there ways of allowing its participation whilst still respecting the parties' rights? The paper argues for a liberal application of the Basson rule. In order to respect fair trial rights, an amicus curiae can be allowed to participate only if the application is made timeously - before the defence positions itself. It can also be limited to written submissions to avoid delays and costs. As far as equality of arms is concerned, a pro-prosecution amicus can be balanced by a pro-accused amicus thus avoiding stacking the odds against the accused.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".