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Record W4398759331 · doi:10.1017/9781009170628.007

What Explains Shareholder Voting?

2024· book-chapter· en· W4398759331 on OpenAlexaff
Bryce C. Tingle

Bibliographic record

VenueCambridge University Press eBooks · 2024
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsShareholderVotingBusinessPolitical scienceFinanceLawCorporate governance

Abstract

fetched live from OpenAlex

This chapter considers the consequences of the low-to-non-existent marginal value of shareholders’ individual voting power in America’s widely held companies. It reviews the empirical literature on rational ignorance and rational irrationality in civic voting. It argues that we should expect similar levels of ignorance and irrationality in shareholder voting. The chapter then considers the evidence for this ignorance and irrationality in: (1) various measures of the value shareholder put on their voting rights; (2) what appears to drive voting outcomes in uncontested director elections; (3) the failure of shareholders to meaningfully hold directors accountable for failures and fraud; (4) the changes in the voting behavior of shareholders once majority voting is introduced; (5) shareholder responses to boards refusing to accept the resignation of a director who loses an election; (6) the evidence that contested director elections (proxy fights) have nothing to do with corporate governance; (7) the ways the economic decisions of shareholders are at variance with their voting behavior; and (8) the evidence shareholders do not pay attention to their own votes, and generally try to keep them purely symbolic.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.012
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.007
Scholarly communication0.0030.006
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0120.002

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 head0.030
GPT teacher head0.186
Teacher spread0.156 · 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 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
Published2024
Admission routes1
Has abstractyes

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