Continuous Auditing: the USA Experience and Considerations for its Implementation in Brazil
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Continuous Auditing, broadly defined as the transformation of internal and external auditing through the application of modern information technology, is being increasingly adopted by firms throughout the world. Organizations ranging from Siemens, HCA, the Royal Canadian Mounted Police, BIPOP Bank and the Internal Revenue Service are developing tools and practices that will bring assurance closer to the transaction and reduce through automation, the cost of auditing. A June 2006 PricewaterhouseCoopers survey finds that 50% of U.S. companies now use continuous auditing techniques and 31% percent of the rest have already made plans to follow suit. In this article we introduce the concepts of CA to a Brazilian audience and discuss its further application there. DOI: http://dx.doi.org/10.4301/s1807-17752006000200007
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it