Bibliographic record
Abstract
This article examines the IFRS strategy by the AcSB, the Canadian setter of GAAP. This strategy changes the GAAP system. Firstly, I investigate how the old GAAP had been developed in Canada, and how USGAAP has influenced Canadian GAAP. Secondly, I research the three standards that were formed into the GAAP system before the adoption of IFRS. The first one instituted a differential reporting system. The second one introduced the application guide of the GAAP. The third one clarified the meaning of the terms “present fairly in accordance with GAAP”. Thirdly, I explicate the strategy plan (2006-2011) that proposed the categorized GAAP system for publicly accountable enterprises (PAE), private enterprises, not-for-profit organizations and pension plans. The AcSB followed a “One size does not necessary fit all” philosophy. For example, PAE are required to adopt IFRS. Last, I analyzed the proper characteristics of the Canadian strategy and the new GAAP systems.
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 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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".