International Financial Reporting Standards and Orientation of Vietnam: “Roadmap & International Experience”
Bibliographic record
Abstract
Currently, the Ministry of Finance is implementing Decision 480/QD-TTG dated 03/18/2013 of The Prime Minister on approving the Strategy Accounting - Audit 2020, Vision 2030 and implementing the Resolution 35/NQ-CP of the Government dated 16.05.2016 related to the support and development of enterprises by 2020. Accordingly, the development and improvement the legal framework of Financial Reporting standards in Vietnam is one of the key tasks and urgent needs to be developed to meet the requirements of the economy in the period of integration. The system of International Accounting Standards, including the International Accounting Standards (IAS) and the standards of international financial reporting (IFRS) was issued, adjusted, updated and replaced by The International Accounting Standards Board. International Accounting Standards is an important condition to ensure that companies and organizations around the world can apply uniform accounting principles in the work of preparing and presenting financial statements. Currently, many countries around the world such as USA, Japan and European countries, Asia Pacific are approaching IFRS convergence trend. In the trend of globalization of accounting, Vietnam will not be outside the process of integration with the system of International Financial Reporting Standards. This article will review the process of formation and development of IFRS, the IFRS trends and the advantages and disadvantages of applying IFRS in Vietnam.
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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 | 0.012 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".