Legal Economics and the Canadian Accredited Investor Standard: Efficiency as a Proxy for Change
Bibliographic record
Abstract
This paper takes a legal-economic approach in assessing the current accredited investor standard that exists as part of Canada’s securities laws. An accredited investor is often characterized as an individual that, due to his or her wealth, may participate in certain investment opportunities that would otherwise not be available. Canada’s National Instrument 45-106 views accredited investors as those with a unique ability to understand financial markets, and due to this level of understanding, the typical disclosure protections afforded to the public—mainly, the prospectus—are not necessary to these individuals. A legal-economic approach to the accredited investor standard looks at the system as constant balance between the benefits enjoyed by those in a position to benefit most from the law as constructed, versus those that are harmed by it. The efficient construction of a law is one that benefits everyone and harms no one. While this is entirely unrealistic to achieve in contemporary society, the goal of any regime should be to come as close to realizing the efficient system as possible—greatest benefits to least amount of harms. This analysis begins by examining the history of the law and its underlying purpose in order to theorize a perfectly efficient ‘ideal system’. How does Canada’s system compare? The analysis takes issue with the current structure of the law, noting that the benefits-to-harms ratio may not be as efficient as is feasible. A better regulatory approach would consider placing less emphasis on wealth as the sole proxy for accreditation. The analysis ends with a list of proposed amendments aimed at increasing the benefits of the system, while decreasing harms as a push toward a more efficient Canadian securities law regime.
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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 | 0.031 | 0.102 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.007 | 0.032 |
| Scholarly communication | 0.015 | 0.010 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".