On How to Strengthen the Application of Management Accounting in Enterprises
Bibliographic record
Abstract
The accounting object of management accounting is the current and future financial movement of the enterprise. The accounting body is the each responsibility center within the enterprise. The accounting background is the external social environment. Conduct rational, scientific and flexible application through the mathematical model, the management theory, the decision theory and the accounting theory, so as to control, forecast, planning, decision-making for enterprises business activities and to improve the economic efficiency of enterprises. Modern management accounting is obvious predictive and forward-looking, which can provide a corresponding reference to enterprise management decision-making. This paper first compares the differences between management accounting and financial accounting from different aspects of accounting subject, different working objectives, different job functions and different working methods. Secondly, it discusses the corresponding measures of promoting the application of management accounting in enterprises, including: It has a certain reference value to establish the concept of application management accounting, the macro market environment optimize and improve the management of accounting staff capacity and quality,
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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 | 0.016 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".