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Record W2126278297 · doi:10.1002/cjas.23

Ownership concentration and corporate governance practices: substitution or expropriation effects?

2007· article· en· W2126278297 on OpenAlexaffvenueabout
Yves Bozec, Richard Bozec

Bibliographic record

VenueCanadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l Administration · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsUniversity of OttawaHEC Montréal
Fundersnot available
KeywordsExpropriationCorporate governanceStock exchangeShareholderArgument (complex analysis)BusinessAccountingIncentiveContext (archaeology)Order (exchange)Index (typography)Monetary economicsEconomicsMicroeconomicsMarket economyFinance

Abstract

fetched live from OpenAlex

Abstract The objective of this study is to analyze the relation between ownership concentration and corporate governance practices of a group of Canadian companies listed on the Toronto Stock Exchange. We rely on the corporate governance index developed by the Report on Business (ROB) in 2002. Our empirical results are consistent with the expropriation effect argument that predicts a negative relation between deviation from the one share‐one vote rule and corporate governance best practices. In this context, the dominant shareholder has incentives to maintain weak internal controls in order to facilitate expropriation. In addition, consistent with prior research, our results give partial support to the substitution effect argument by showing a negative impact of ownership concentration on the board composition subindex. Copyright © 2007 ASAC. Published by John Wiley & Sons, Ltd.

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)0.018
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.128
GPT teacher head0.304
Teacher spread0.176 · 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 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

Citations109
Published2007
Admission routes3
Has abstractyes

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