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Record W2182758244

Board Size, CEO Duality, and the Value of Canadian Manufacturing Firms

2011· article· en· W2182758244 on OpenAlexaffabout
Amarjit Gill, N. D. Mathur

Bibliographic record

VenueJournal of Applied Finance and Banking · 2011
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsChief executive officerBusinessStock exchangeValue (mathematics)Sample (material)Enterprise valueDuality (order theory)ManufacturingAccountingIndustrial organizationMarketingEconomicsFinanceManagement
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this study is to examine the impact of board size and the CEO (Chief Executive Officer) duality on the value of Canadian manufacturing firms. A sample of 91 Canadian manufacturing firms listed on Toronto Stock Exchange (TSX) for a period of 3 years [from 2008-2010] was selected. The co-relational and non-experimental research design was used to conduct this study. The empirical results show that larger board size (large number of directors) has a negative impact on the value of Canadian manufacturing firms. The findings also show that the CEO duality has a positive impact on the value of Canadian manufacturing firms. In addition, firm size, firm performance, and potential growth of the firm positively impact on the value of Canadian manufacturing firms. This study contributes to the literature on the factors that affect value of the firm. The findings may be useful for the financial managers, investors, and financial management consultants.

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)0.001
metaresearch head score (Gemma)0.007
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 score0.084
Threshold uncertainty score0.169

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0020.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.181
Teacher spread0.165 · 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

Citations58
Published2011
Admission routes2
Has abstractyes

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