Culture, Economics and Disclosure of (IAS/IFRS) Information: Empirical Evidence in the Tunisian, French and Canadian Contexts
Bibliographic record
Abstract
According to the theory of environmental determinism, the accounting system of a country is made by the environment. From our study on three samples of the three countries in different cultural and economic environments (50 Tunisian firms listed on Tunindex, 35 French companies listed on the CAC40 and 36 Canadian companies listed on TSE60), we have demonstrated that despite the adoption by these three countries in a single repository (IAS / IFRS), the degree of implementation of these standards (for each standard) differs from one country to another. We have also found that the level of IAS/IFRS disclosure in Canada is higher than in France which is in far higher than in Tunisia turn. The high level of disclosure of TSE60 companies of Canada compared to the CAC 40 companies of France is explained by existing differences between the cultural dimensions of the two countries. Indeed, Canada is characterized by professionalism and transparency in contrast to France which is characterized by the statutory control and discretion. In addition, for Tunisia, extensive reading annual reports showed a low level of disclosure and demonstrated the presence of a large number of items unenforceable. Inapplicable items reflect the absence of the scope of the standards adopted by Tunisia. Thus, standards adopted and those not yet adopted by Tunisia face rather the level of economic development as the national culture. The results of this study demonstrate the validity of the theory of environmental determinism. Keywords: Theory of environmental determinism, Disclosure, IAS/IFRS.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".