Probe into Reasons of Financial & Statistical Accountings Integration and Discussion of Conception L'ETUDE SUR LE CONCEPT DE L'INTEGRATION DE L'APUREMENT COMPTABLE ET L'APUREMENT STATISTIQUE
Bibliographic record
Abstract
As national economy’s accounting system improves and perfects day by day, financial accounting and statistical accounting, two of the three major accounting components, communicate with each other more and more tightly. To probe into how to strengthen the communication between financial and statistical accountings and seek for the establishment of integrated pattern for financial and statistical accountings will largely improve economic accounting efficiency, reduce economic accounting cost and increase the service value of economic accounting achievements. In this paper the authors analyzes the necessities and conditions of financial and statistical accountings and propose of constructive conception for improving financial and statistical accountings integration based on the exploration and definition of financial and statistical accountings integration with the help of discussion over relationship between financial and statistical accountings.Key Words: Financial Accounting; Statistical Accounting; Integration
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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 | 0.018 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.005 | 0.032 |
| Scholarly communication | 0.015 | 0.014 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".