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Record W7027240769

Canada: Governing the Future for Investor Confidence

2004· article· en· W7027240769 on OpenAlexaboutno aff

Bibliographic record

VenueSMU Scholar (Southern Methodist University) · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsPublicityScrutinyCapital marketEquity (law)Capital (architecture)Liberian dollarEvent study
DOInot available

Abstract

fetched live from OpenAlex

From late 2001 through 2002, corporate fraud and scandal dominated business headlines in the United States, resulting in a serious decline in investor confidence.' Enron Corporation's failure, in particular, proved to be a monumental business event because the company was so large and esteemed. 2Unfortunately, this event was the first of several corporate humiliations.In addition to Enron, companies such as WorldCom, Adelphia, Arthur Andersen, Martha Stewart Living Omnimedia, and Tyco captured similar negative publicity during the parade of scandals. 3Consequently, many questions surfaced regarding the integrity of capital markets and related participants, including company executives, directors, and external auditors. 4Because of the United States' central economic role, these collapses also impacted the rest of the world.In North America alone, trillions of dollars disappeared from the marketplace, both in company worth and in investors fleeing the equity and mutual fund markets. 5 As a result of these losses, many legislators, lawyers, and jurists voiced various opinions with regards to the future of corporate and securities law.Many countries have radically restructured their regulatory systems or are in the process of doing so.In particular, Canada, the United States' northern neighbor, received increased scrutiny regarding the country's regulatory structure for capital markets.As a result, Canada took several initiatives, not all of which are collaborative, that attempt to restore confidence and give the country's capital markets a national and international competitive advantage.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.966
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.020
GPT teacher head0.252
Teacher spread0.231 · 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.

Study designNot applicable
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

Citations0
Published2004
Admission routes1
Has abstractyes

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