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Record W158195819

A Canadian Model of Corporate Governance: Where Do Shareholders Really Stand?

2014· article· en· W158195819 on OpenAlexaboutno aff
Carol Liao

Bibliographic record

VenueeYLS (Yale Law School) · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Insolvency and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsCorporate governanceCorporate lawShareholderAccountingCorporationBusinessStakeholderPolitical scienceLaw and economicsLawEconomicsFinance
DOInot available

Abstract

fetched live from OpenAlex

This feature article in the Director Journal summarizes the findings from the report, "A Canadian Model of Corporate Governance: Insights from Canada's Leading Legal Practitioners," produced for the Canadian Foundation for Governance Research and the Institute of Corporate Directors (also available on SSRN). In the report, interviews were conducted with 32 leading senior legal practitioners across Canada to opine on the fundamental principles that are driving the development of Canadian corporate governance. The report found that Canadian common law has made the process of considering stakeholders in the "best interests of the corporation" more overt, well beyond what is assumed in Anglo-American corporate legal scholarship. Layered onto this corporate legal base, the securities commissions are now playing a major role in shaping Canadian corporate governance practices, and their influence has pushed Canada toward a more shareholder-centric model of governance. Securities regulators have increased shareholders’ rights well beyond what has ever been contemplated under Canadian corporate law. It remains to be seen from the pending determinations by the Canadian Securities Administrators on the regulation of poison pills as to whether the regulators will be tempering their positions toward shareholder primacy in the future.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.118
Threshold uncertainty score0.857

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0170.016
Scholarly communication0.0130.005
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.000

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 head0.022
GPT teacher head0.203
Teacher spread0.181 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2014
Admission routes1
Has abstractyes

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