From IDA to IIROC: Has self‐regulation in the Canadian investment industry evolved?
Bibliographic record
Abstract
Abstract This article analyzes the enforcement practices of the Investment Industry Regulatory Organization of Canada (IIROC) and compares them with its predecessor, the Investment Dealers Association of Canada (IDA). The study collected data from IIROC's tribunal cases decided between June 2008 and December 2019 and compared them with data on the IDA's enforcement of complaints from 1984 to 2008. The findings reveal no statistically significant difference in the fines imposed by the two regulatory bodies. Furthermore, IIROC has refrained from issuing lenient penalties such as retaking examinations/courses or mandating terms and conditions for offenders. The results also indicate no significant impact on the number or distribution of offense types committed in the industry over time. Most notably, the Ontario Securities Commission, the Canadian Securities Regulators, and the new Self‐Regulatory Organization of Canada should consider these findings when formulating policies concerning the role of self‐regulation in the financial markets.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".