A multinational test of determinants of corporate disclosure
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.
Bibliographic record
Abstract
This paper develops a model of cultural, national, and corporate factors that influence the financial disclosure of corporations. This model is then tested empirically using a sample of companies from 33 countries. The paper extends the literature on disclosure by considering a larger number of variables that represent determinants of disclosure and by empirically testing the model using a larger number of countries than prior studies. The model is tested using disclosure scores included in International Accounting and Auditing Trends. The model considers the influence of culture, national political and economic systems, and corporate financial and operating systems on the amount of corporate financial disclosure. The results of the regression model indicate that disclosure is influenced by culture, national systems, and corporate systems. The model developed is shown to provide a reasonably good explanation of the disclosure decision. Differences among the components of the model help explain differences in observed financial disclosure between companies in different countries and between companies within the same country. The results indicate that the financial-disclosure decision for a company is complex and influenced by many national and corporate factors.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it