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Record W1984774844 · doi:10.1177/2277977914548340

Board Composition and Governance Dilemma at Magna International

2014· article· en· W1984774844 on OpenAlexaffabout
Eduardo Schiehll, Gokhan Turgut, Elise Demers

Bibliographic record

VenueSouth Asian Journal of Business and Management Cases · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsAccountingCorporate governanceBusinessShareholderDilemmaDatabase transactionComposition (language)Corporate lawPublic relationsFinancePolitical science

Abstract

fetched live from OpenAlex

The primary subject matter of this case study is board composition and the governance roles of the board of directors in publicly traded companies. It is designed to supplement a text chapter or other material on the monitoring and advisory roles of directors and how board structure and composition impact these roles. The case is also designed to allow students to identify and assess governance issues related to firm ownership structures, family-owned or controlled companies, ethical conduct of the board of directors and conflicts between majority and minority shareholders. The case is sufficiently detailed to allow discussing the multidimensional aspects of board composition (or board diversity), including gender, ethnicity, expertise, experience and prestige. It is structured as a chronological description of the controversy generated by a proposed related party transaction (a buyout transaction) designed to dismantle a dual-share capital structure that allowed the Stronach family to control the company (Magna International Inc.) with just a fraction of its equity. The case can serve as the basis for both short case assignments and class discussions. It is appropriate for undergraduate and graduate courses in strategic management, leadership, corporate governance and financial accounting. The topic is relevant and current, as it can be related to the ongoing reforms of Canadian corporate governance practices for controlling shareholders and related party transactions.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.288
Threshold uncertainty score0.576

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 head0.011
GPT teacher head0.190
Teacher spread0.180 · 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 designObservational
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

Citations2
Published2014
Admission routes2
Has abstractyes

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