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Record W4231055323 · doi:10.1504/ijaf.2015.076175

Monitoring role of the board and ownership concentration: from interests misalignment to expropriation

2015· article· en· W4231055323 on OpenAlexaffabout
Richard Bozec, Mohamed Dia

Bibliographic record

VenueInternational Journal of Accounting and Finance · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsLaurentian UniversityWilfrid Laurier UniversityUniversity of Ottawa
Fundersnot available
KeywordsExpropriationIndependence (probability theory)VotingShareholderAccountingPanel dataCash flowSample (material)BusinessCorporate governanceEmpirical evidenceMonetary economicsEconomicsPoliticsFinanceLawEconometricsMarket economyPolitical scienceStatistics

Abstract

fetched live from OpenAlex

Despite all the value placed on the independent director by financial market participants and regulators, empirical evidence on the relation between board independence and firm performance is largely inconclusive. The objective of this paper is to revisit the board independence-performance relationship while taking into account the ownership structure of the firm. The study is conducted over a four-year period (2002-2005) using panel regressions on a sample of Canadian publicly traded companies (502 firm-year observations). The results show a positive and significant relationship between board independence and Tobin's Q only when ownership is concentrated in the hands of a controlling shareholder (legal control). The highest level of separation between voting and cash flow rights is also found in controlled entities. The greater the gap between voting and cash flow rights, the stronger the relationship between board independence and performance. Overall, evidence supports the expropriation effect argument.

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 score0.016
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.021
GPT teacher head0.232
Teacher spread0.211 · 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

Citations1
Published2015
Admission routes2
Has abstractyes

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