Pathology of Accounting Systems and Financial Reporting of Small Business
Bibliographic record
Abstract
Achieving the management in every economic unit needs having reliable and in time information. Proving to be true requires establishing a suitable accounting system for collecting, processing and reporting the effects and results of activities and exchanging them around the environment of the economic establishment activation. The initial consideration indicates that a great part of some small economic establishments Haven’t hat suitable accounting systems to providing timely and reliable information for achieving the responsibility of responding and helping the management decision making process. Base on these the first and main gold of current study is to pathology the accounting systems and financial reporting in small companies. Statistical sample of these studies has been chosen among small but active companies in economical environment in sistan and bluchestan and during the financial periods from 2007 to 2009. The study findings shows that some factors like employees experience in financial parts, the space between business needs of the accounting employees and collegiate training in relevant fields, suitable systems of compensation for the employees service in financial parts and the management awareness of financial subject in business units , is directly relation with the efficiency of accounting systems and financial reporting . and some factors like scientific competency and legal and contractual necessities in attracting the employees in financial units and taxation controls on the company’s financial activation doesn’t have any significant relation whit efficient of accounting systems and financial reporting.
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".