The Jury is Out: The Controversy About Jury Trials Under the Alberta Securities Act
Bibliographic record
Abstract
After reviewing the place of securities law enforcement within the Canadian court system, the author traces the Peers and Aitkens decisions from the Provincial Court to the Supreme Court and outlines how these cases dealt with the question of what penalties trigger the right to a jury trial under section 11(f) of the Charter. The author explains how section 11(f) impacts the division of powers by creating a constitutional cap on the prison sentences that are available for violations of provincial law. In light of stiff maximum penalties for violations of securities laws, the Peers and Aitkens decisions raise the question of whether there are constitutional reasons to continue to try regulatory offences by judge alone in provincially appointed courts.
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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 | 0.027 | 0.072 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.014 | 0.024 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.011 | 0.012 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".