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Record W7046391993

Corporate governance and the judicial license to tailor a remedy for oppression : the oppression remedy in Canada

2002· dissertation· en· W7046391993 on OpenAlexaboutno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2002
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicSuperconducting and THz Device Technology
Canadian institutionsnot available
Fundersnot available
KeywordsOppressionCorporate governanceStatutory lawDiscretionOrder (exchange)License
DOInot available

Abstract

fetched live from OpenAlex

One of the most important issues that arise under the statutory oppression remedy is the manner in which a court will use its wide powers to order relief once oppression has been found. Guidelines according to which courts will exercise their discretion become even more desirable where a remedy may impact on the governance structures of the corporation. There is an extensive body of case law under the oppression remedy, most of which tends to relegate the exercise of the remedy to the facts of a case. However, from a study of the case law, two principles appear with varying frequency depending on the size of the corporation. These are principles which may be asserted under the oppression remedy. The first principle states that the majority may not exercise its electoral rights to the prejudice of the minority. It flows from the relationship between members of a corporation and arises most frequently at closely held corporations. The second principle is against abuse of fiduciary position, which entails a duty on directors and senior management to protect the interests of all shareholders. Abuse of fiduciary position may also involve instances where there is a breach of fiduciary duties to the corporation. This second principle is more prevalent at widely held corporations. The remedy will be tailored according to the principle under which liability was found.

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)0.003
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.096
Threshold uncertainty score0.700

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0180.011
Scholarly communication0.0100.002
Open science0.0020.003
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0070.000

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 head0.230
Teacher spread0.209 · 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 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
Published2002
Admission routes1
Has abstractyes

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