Bibliographic record
Abstract
The U.S. Sarbanes-Oxley Act (SOX) was enacted in 2002 in response to a number of well-publicized corporate scandals. The purpose of the Act is to protect the interests of investors by addressing several concerns including: the certification of financials, disclosure requirements, and auditing and corporate governance standards.\nCurrently, SOX applies to all issuers whose securities are listed in the U.S. or who are required to file annual or periodic reports with the SEC - including Canadian companies reporting under the Canada-U.S. Multi-jurisdictional Disclosure System.\nThis publication is geared specifically to those who advise Canadian companies that engage or plan to engage in capital market activity in the U.S. The text of the legislation, the SEC rules and form requirements are organized by subject matter, and each subsection of this book opens with commentary and analysis of selected sections of the Act, along with new or amended SEC rules, amended or new sections of the Exchange Act of 1934, certain SEC forms and relevant criminal code sections. It also addresses the regulation of the accounting profession as it intersects with the new rules for reporting companies
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.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.161 | 0.074 |
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".