Testing the Level of Compliance of International Accounting Standard IAS 38: Evidence from Bahrain
Bibliographic record
Abstract
This research aims to examine the level of compliance of International Accounting Standard 38 (IAS 38, intangible assets) among the listed companies of Bahrain Bourse. This paper employs the method of equal weighted disclosure index to determine if the listed firms are complying with the disclosure requirements of the IAS 38. The required data for the year 2016 has been obtained from Bloomberg. The research found that firms have a compliance of 35.4%. The regression analysis results showed that there is a correlation between IAS 38 disclosure and the size of audit firms, leverage, profitability and industry type. There is a lack of relationship between IAS 38 disclosure and age & size of the company. This research serves as the basis of a future study on IAS 38 in different countries in emerging markets.In order to assure high performance and implementation of IAS 38, all firms listed in Bahrain Bourse ought to increase the level of compliance.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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 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".