Regulatory Capture Of Self-Regulatory Organizations (SROs) In Canada: Do SROs Serve Public Or Industry Interests?
Bibliographic record
Abstract
The Canadian securities industry relies heavily on self-regulation, with two self-regulatory organizations (SROs), the Investment Industry Regulatory Organization of Canada (IIROC) and the Mutual Fund Dealers Association of Canada (MFDA) regulating the industry. The former regulates all investment dealers and trading on Canada's debt and equities markets, while the latter governs domestic distributors of mutual funds, except fixed-income products. As expected in an SRO model of regulation, the structure of both IIROC and the MFDA presents a risk that industry members may influence or capture its operations, advancing industry interests at the cost of its public interest mandate.\nThis Article examines the current regulatory framework of IIROC and the MFDA, including their corporate governance structure and enforcement mechanisms. It finds that the existing structure of both SROs could favor industry interests above investors' (public) interests, as there are few safeguards in place to avoid the conflict of interests that is inherent to adopting an SRO structure.\nGiven the deficiencies in the current regulatory system, this Article assesses the implications of the proposed merger of IIROC and the MFDA into a single new SRO, concluding that it is a positive development. However, to effectively address the public's concerns with the current structure, this Article emphasizes the need for a more investor-focused approach in designing the new SRO regulatory framework and more robust monitoring of the new SRO by the Canadian Securities Administrators.
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".