MétaCan
Menu
Back to cohort
Record W2890550585 · doi:10.3386/w12525

The Corporate Governance Role of the Media: Evidence from Russia

2006· preprint· en· W2890550585 on OpenAlexaff
Alexander Dyck, Natalya Volchkova, Luigi Zingales

Bibliographic record

VenueNational Bureau of Economic Research · 2006
Typepreprint
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Finance and Governance
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCorporate governanceBusinessAccountingPolitical scienceFinance

Abstract

fetched live from OpenAlex

We study the effect of media coverage on corporate governance by focusing on Russia in the period 1999-2002.This setting offers us three ideal conditions for such a study: plenty of corporate governance violations, no alternative mechanisms to address them, and the presence of an investment fund (the Hermitage) that actively lobbies the international press to shame companies perpetrating those violations.We find that Hermitage's lobbying is effective in increasing the coverage of corporate governance violations in the Anglo-American press.We also find that coverage in the Anglo-American press increases the probability that a corporate governance violation is reversed.This effect is present even when we instrument coverage with an exogenous determinant, i.e. the Hermitage's portfolio composition at the beginning of the period.The Hermitage's strategy seems to work in part by impacting Russian companies' reputation abroad and in part by forcing regulators into action.

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)0.006
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 score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
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 head0.207
GPT teacher head0.375
Teacher spread0.168 · 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

Citations13
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueNational Bureau of Economic ResearchSame topicCorporate Finance and GovernanceFrench-language works237,207