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Record W3122604797

Legal Origins, Investor Protection, and Canada

2009· article· en· W3122604797 on OpenAlexaffabout
Poonam Puri

Bibliographic record

VenueeYLS (Yale Law School) · 2009
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicState Capitalism and Financial Governance
Canadian institutionsYork University
Fundersnot available
KeywordsJurisdictionCapital marketIssuerCommon lawLawEnforcementCivil law (Civil law)Political scienceFinancial marketCapital (architecture)Government (linguistics)Commercial lawEconomicsBusinessFinanceGeography
DOInot available

Abstract

fetched live from OpenAlex

In Legal Determinants of External Finance, Rafael La Porta, Florencio Lopez-de-Silanes, Andrei Shleifer, and Robert Vishny (“LLSV”) argue that the reason that some countries have bigger capital markets than others can be traced to the legal origin of the country, i.e. whether it is a common law or a civil law jurisdiction. This paper explores the LLSV thesis in the context of Canada, which is a common law jurisdiction that also is home to Quebec which has a civil law tradition.Three issues are examined in this paper: first, how and why Canada fared relatively well in the recent financial crisis, second, why Canada has not yet created a national securities regulator, and third, how Quebec, a civil law jurisdiction, operates within an overarching common law framework, and the implications of this cross-fertilization of systems.These three issues are explored by examining the development of various investor protection laws and structures over time in Canada (as opposed to examining investor protection laws at a point in time, as the LLSV studies do), and also by providing context to explain why certain rules and structures have been adapted and others, while economically efficient, may have been rejected. In Canada, as in many other jurisdictions, securities laws and securities structure have an impact on investor protection, as do banking laws and the banking regulatory framework and business culture. Not all investor protection mechanisms are located in the corporate statutes, as LLSV assumes. LLSV did not explore securities law rules, securities law structures, or banking laws. As well, the Canadian system is both structured in such a way and has evolved in such a way that investor protections are fairly consistent between the common law and civil law provinces, even when the civil law statute does not necessarily mimic the common law statute.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.931
Threshold uncertainty score0.584

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.009
GPT teacher head0.192
Teacher spread0.183 · 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 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

Citations4
Published2009
Admission routes2
Has abstractyes

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