Annual report IC disclosures in The Netherlands, France and Germany
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
Purpose This paper replicates and extends the Bontis research on intellectual capital (IC) disclosures in Canadian companies and also elaborates on the Beaulieu et al. research on disclosures by Swedish firms. Design/methodology/approach The paper studies IC disclosures by French CAC‐40, Dutch AEX and German XETRA‐DAX publicly‐listed companies for the years 2000 and 2001. The paper also discusses country‐specific arguments in favour of and against voluntary disclosure by such companies and searches both the annual reports and financial statements for IC hits. Findings Applying the Gray‐scale to categorise countries, the paper finds not only that voluntary IC disclosure significantly differs between these countries, but also that this difference can be explained by country‐specific regulation and auditor conservatism. Research limitations/implications The paper only studies Dutch, French and German IC disclosures in annual reports and financial statements. These three countries are European Union member states but “differ” significantly from one another. The differences discussed in this paper, however, are by no means exhaustive, nor do they picture the “European situation” in full. Practical implications The paper recognises that the intangible nature of IC creates tension with current country‐specific legislation and strongly calls for convergence of applicable accounting standards and practices because of the increasing importance of IC and because of the improvement of corporate governance and policy making. Originality/value The paper not only extends (or fine‐tunes) previous research, but also links with the literature that discusses the consequences of country‐specific characteristics for accounting standards and 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.
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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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