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Record W2963896371 · doi:10.5430/afr.v8n3p136

Testing the Level of Compliance of International Accounting Standard IAS 38: Evidence from Bahrain

2019· article· en· W2963896371 on OpenAlexvenueno aff
Mohammed Saeed Hassan, Adel Sarea, Gagan Kukreja

Bibliographic record

VenueAccounting and Finance Research · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsnot available
Fundersnot available
KeywordsAccountingBusinessLeverage (statistics)Profitability indexAuditOrder (exchange)Compliance (psychology)Index (typography)Finance

Abstract

fetched live from OpenAlex

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.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.170
GPT teacher head0.346
Teacher spread0.176 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2019
Admission routes1
Has abstractyes

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