Discussion on the Training of the Talented Persons on Forensic Accounting in Higher Education
Bibliographic record
Abstract
Originating from the US in the 1970s,forensic accountancy is a burgeoning branch of learning.Our country merely started its research in this field at the end of the 20th century.Since the unexpected collapse of Enron and Andersen corporations,the significance of forensic accounting is becoming ever more prominently important.Under the influence,the marketing demand for the accountant is increasing rapidly and so is the payment.In comparison,making a comprehensive survey on our country's present accounting education,however,the education of forensic accountancy is apparently not receiving adequate emphasis from the government.No matter in the aspect of the building of academic subject or in the teaching practice,the input and attention is far from enough.Therefore by drawing on the experience of Canada's and America's education on forensic accounting,this thesis discusses several feasible ways to forester the talented persons on forensic accounting.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".