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Record W3123229838 · doi:10.1111/1467-646x.00097

Firm‐level Disclosures and the Relative Roles of Culture and Legal Origin

2003· article· en· W3123229838 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of International Financial Management and Accounting · 2003
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHofstede's cultural dimensions theoryExplanatory powerOperationalizationUnivariateLegal cultureOrganizational cultureSample (material)Multivariate statisticsBusinessSocial psychologyPsychologyAccountingPolitical sciencePublic relationsLawStatistics

Abstract

fetched live from OpenAlex

Abstract In this paper, I investigate the relative roles of legal origin and national culture in explaining firm‐level disclosure levels internationally. Using a significantly larger and more representative sample than prior research, I document, using univariate and multivariate analyses, that both legal origin and culture (as operationalized by Hofstede and Schwartz) are important in explaining firm disclosure. Neither legal origin nor culture dominates with respect to overall explanatory power for variations in disclosure levels. Consequently, it is premature to write off culture as an important factor in the financial reporting environment. Furthermore, I find that legal origin is an important conditioning variable for the role of culture. Finally, although legal origin is a key determinant of disclosure levels, I hypothesize and find that its importance decreases with the richness of a firm's information environment.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.846
Threshold uncertainty score0.523

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.008
GPT teacher head0.217
Teacher spread0.210 · 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