Probe into the Reasons of Absence in Accounting Credit among Listed Companies and Study on Countermeasures/L'ORIGINE DU MANQUE D'HONNETETE DE LA COMPTABILITE DES ENTREPRISES COTEES ET L'ETUDE SUR LES CONTRE-MESURES
Bibliographic record
Abstract
Credit is basic principle for accounting and the absence of accounting credit will restrain enterprises from existing and development and influence the healthy operation of national economy. Currently absence in accounting credit is an international problem and the accounting credit of listed companies is suffering from social questioning. In this paper, the authors, based upon the definition and performance of absence in accounting credit among listed companies with the help of systematic thoughts, deeply and completely analyzes both internal and external reasons for the absence in accounting credit among listed companies, and attempt to propose of corresponding countermeasures in punishing absence in accounting credit from the aspect of government regulation, social supervision and self-discipline of enterprises and accounting personnel so as to put forward related references for accounting credit construction among listed companies.Key Words: Listed Company; Absence in Accounting Credit; Probe into Reasons; Countermeasures
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".