Suing anonymously : when is the personal price to pay for justice too high?
Bibliographic record
Abstract
Justice is served both by openness and by access, but these two values may in some cases be in need of careful balancing. Such cases would be, for instance, where the personal psychological harm to a prospective plaintiff of having her identity as plaintiff disclosed to the public would effectively bar her from launching the civil action in court. In appropriate cases, the solution would be to grant an anonymity order to the prospective plaintiff. However, there is no direct authority in South African law on the granting of anonymity orders in civil cases in general, which causes uncertainty that is not in the interest of justice. As such, I analyse the comprehensive test for the granting of confidentiality orders (which include anonymity orders) in civil cases that has been developed in Canadian law, namely the Sierra Club test. In brief, this test entails that an anonymity order should only be granted if such anonymity order is (a) necessary, and (b) proportional to its purpose. I conclude that the Sierra Club test could fruitfully be applied in our law.
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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 | 0.013 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.024 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.013 | 0.009 |
| Insufficient payload (model declined to judge) | 0.007 | 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".