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Record W28449830

Who Watches the Watchers? The Securities Investor Protection Act, Investor Confidence, and the Subsidization of Failure

2010· article· en· W28449830 on OpenAlexfundno aff
Thomas Wuil Joo

Bibliographic record

VenueSSRN Electronic Journal · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Insolvency and Governance
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsBusinessInvestor protectionInsolvencyFinanceSubsidyCorporationOrder (exchange)EconomicsMarket economyCorporate governance
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.008
GPT teacher head0.177
Teacher spread0.169 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2010
Admission routes1
Has abstractyes

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