A Comparative Synopsis of the Enforcement of Market Abuse Prohibition in Australia and South Africa
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In Australia, the market abuse prohibition is generally well accepted by the investing and non-investing public as well as by the government. This co-operative and co-ordinated approach on the part of all the relevant stakeholders has to date given rise to an increased awareness and commendable combating of market abuse activities in the Australian corporations, companies and securities markets. It is against this background that this article seeks to explore the general enforcement approaches that are employed to combat market abuse (insider trading and market manipulation) activity in Australia. In relation to this, the role of selected enforcement authorities and possible enforcement methods which may be learnt from the Australian experience will be isolated where necessary for consideration in the South African market abuse regulatory framework.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it