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Record W7098811547

Toronto

2005· article· en· W7098811547 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBioenergy crop production and management
Canadian institutionsnot available
Fundersnot available
KeywordsCorporate governanceVotingShareholderDual (grammatical number)Equity (law)Capital structureAgency costDifferential (mechanical device)Agency (philosophy)
DOInot available

Abstract

fetched live from OpenAlex

This paper looks beyond agency theory and utilizes multiple theoretical lenses to explore governance in firms adopting dual class share structure. A model is offered that proposes dual class share structure as a contingent governance mechanism. Governance is asserted to operate at individual, industry and national levels under different rationales. This paper attempts to investigate the theoretical underpinnings for the reasons why firms frequently adopt the dual class equity structure, i.e. a capital (or ownership) structure based on the issuance of shares with differential voting rights (DeAngelo et al. 1985). Such an ownership structure is justified by some researchers as a defensive structure adopted by the directors and managers of a firm to prevent hostile acquisitions and takeovers by corporate raiders (Grossman and Hart, 1988; Harris and Raviv, 1988), and as a means of wealth enhancement of all shareholders (Alchain & Demsetz, 1972; Gromb 1993; Zingales, 1995). Many researchers however, assert that dual class shares are a mechanism by which insiders expropriate value from the minority shareholders, extract private benefits of control and ensure managerial entrenchment (Jarrell and Poulson, 1988; Gompers et al., 2004). The rationale for both of these assertions, as for most

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.409
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0060.003
Open science0.0020.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.5910.335

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 head0.010
GPT teacher head0.192
Teacher spread0.182 · 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.

Study designNot applicable
Domainnot available
GenreOther

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
Published2005
Admission routes1
Has abstractyes

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