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
The Sino-Forest Case provides a real-world example of financial misstatement and audit failure.2 The case encompasses related parties, auditing procedures for tangible assets, and internal controls. Sino-Forest Corporation was engaged primarily in the purchase and sale of standing timber in the People’s Republic of China (PRC). The principal executive office was in Hong Kong and its securities were traded on the Toronto Stock Exchange until 2011. The management of Sino-Forest created a complex web of subsidiaries and related entities whereby it controlled the purchase and sale of standing timber in widely dispersed regions of the PRC. Sino-Forest personnel created false documents related to these transactions, which were materially misstated in the company’s financial statements. Sino-Forest auditors failed to properly recognize and deal with these misstatements, despite concerns expressed by members of the audit team about a lack of evidence regarding the standing timber assets. As a result of these problems, the company was delisted from the Toronto Stock Exchange and is now defunct.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| 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