Who Watches the Watchers? The Securities Investor Protection Act, Investor Confidence, and the Subsidization of Failure
Bibliographic record
Abstract
The Securities Investor Protection Act of 1970 (SIPA) created a special scheme for the liquidation of insolvent securities brokerage firms and established the Securities Investor Protection Corporation (SIPC) to administer a fund to protect the customers of failed brokers. SIPA is primarily designed to passively reimburse customers for losses due to broker failures and to thereby boost public confidence in securities markets. This Article argues that in order to truly operate as an scheme, SIPA should take an active role in the prevention of brokerage failures, rather than merely attempting to alleviate the harms caused by such failures. SIPA currently shifts much of the cost of broker failures away from the securities brokerage industry, thereby subsidizing it. SIPA should assign more of these costs to the brokerage industry. Such an arrangement is more consistent with the self-regulated nature of the industry. It is also more fair, in that the industry reaps the benefits of SIPA investor protection in the form of investor confidence, and more efficient in that assigning the costs to the best cost-avoider is a more efficient means to long-term customer protection and industry health.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".