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Chinese Accounting Standards Convergence with International Financial Reporting Standards

2024· article· en· W4403582320 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAdvances in Economics Management and Political Sciences · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAccounting Theory and Financial Reporting
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAccountingAccounting standardFinancial accountingConvergence (economics)International Financial Reporting StandardsBusinessAccounting information systemEconomics

Abstract

fetched live from OpenAlex

As the global economy becomes more integrated, Chinese Accounting Standards (CAS) are gradually moving towards convergence with International Financial Reporting Standards (IFRS). So far, CAS and IFRS do still have a number of variations including content, format and setup mechanisms. This paper analyzes three main differences in the content between CAS and IFRS regarding the financial instrument, biological asset, and lease measurement. These differences may cause problems for international practitioners and investors. In addition, the paper discusses the influences of the global convergence of CAS and the challenges faced by the technology industry, listed companies, and government. It is recommended that China need to consider the domestic economic situation and policies when adopting IFRS, and properly adjust the content of the standard accordingly, so as to better meet the domestic needs and development prospects. And industries should balance convergence and market challenges and work together to shape a practical and comprehensive China accounting system to enable China to develop globally further.

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.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.470
Threshold uncertainty score0.918

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.004
Open science0.0000.000
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 head0.008
GPT teacher head0.292
Teacher spread0.284 · 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