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Record W2031884957 · doi:10.5430/afr.v3n3p12

The Effects of Various Choices of IFRS Implementation on the Relevance of Accounting Information

2014· article· en· W2031884957 on OpenAlexvenueaboutno aff
Mohamed Rachid Ouezzani, Youssef Alami

Bibliographic record

VenueAccounting and Finance Research · 2014
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsnot available
Fundersnot available
KeywordsRelevance (law)AccountingBusinessInternational Financial Reporting StandardsAccounting information systemChinaSample (material)Process (computing)Convergence (economics)EconomicsPolitical scienceComputer scienceEconomic growth

Abstract

fetched live from OpenAlex

To adopt IFRS, some jurisdictions as South Africa has chosen a method of implementation IFRS by the adoption of the IASB process while others like Canada, South Korea and the European Union countries opted for outstanding by standard method to implement IFRS. China preferred an incomplete transposition of these standards to the international reference. Faced with these various choices, the question of the impact of the IFRS implementation on the relevance of accounting information remains posed. To answer this question, we have studied the evolution of the relevance of accounting information following the adoption of the IFRS implementation method for a sample composed of listed companies. These firms are from six countries which have opted for different implementation methods of IFRS. The results show a maintain of the high relevance of accounting information for South Africa which opted for an implementation process and an improvement of the relevance for countries which has adopted a standard by standard method of IFRS implementation such as Canada, Germany and Spain excepting South Korea. In China, which conducted an extensive but incomplete convergence of its standards to IFRS, the results demonstrate a decrease in the relevance of the accounting information. Also, comparative analysis of the results shows a better relevance of accounting information for countries which have opted for methods of implementation fairly close to the IFRS.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.020
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.710
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.011
GPT teacher head0.277
Teacher spread0.266 · 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 teacher head, not a consensus.

Study designOther design
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

Citations2
Published2014
Admission routes2
Has abstractyes

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