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Record W2587072088 · doi:10.22495/cocv10i3c1art3

Executive compensation and board of directors’ disclosure in Canadian publicly-listed corporations

2013· article· en· W2587072088 on OpenAlexaboutno aff
Martin Spraggon, Virgínia Bodolica, Tor Brodtkorb

Bibliographic record

VenueCorporate Ownership and Control · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsnot available
Fundersnot available
KeywordsAccountingCorporate governanceBusinessExecutive compensationTransparency (behavior)Proxy (statistics)Order (exchange)Compensation (psychology)LegislationExecutive orderFinancePolitical sciencePublic administrationLawPsychology

Abstract

fetched live from OpenAlex

This article contributes to the growing body of literature exploring the important role that information transparency plays in strengthening the national corporate governance regime. We review the 2007 amendments to the Canadian reporting legislation with the particular emphasis on sections pertaining to executive compensation and boards of directors. Taking into consideration the specificities of the „comply-or-explain‟ system in Canada, we seek to uncover the extent to which publicly-listed firms comply with these newly amended standards of corporate governance reporting. Based on a comparison of 403 proxy circulars issued in the post-amendment period, we identified important cross-firm variations in the type and format of disclosed information on executive compensation and corporate boards of directors. In order to address the problems that inter-organizational disclosure discrepancies generate for governance researchers and analysts, we provide several recommendations on how Canadian publicly-traded companies can improve their reporting practices

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)0.004
metaresearch head score (Gemma)0.035
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 score0.073
Threshold uncertainty score0.526

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.035
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.008
Science and technology studies0.0030.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.017
GPT teacher head0.190
Teacher spread0.173 · 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

Citations6
Published2013
Admission routes1
Has abstractyes

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