Bibliographic record
Abstract
ABSTRACT Using Ross Skinner's 1995 CA Magazine article, “Judgment in Jeopardy", as a stepping stone, we revisit the meaning of professional judgment in accounting in light of developments in standard setting, financial markets, and business operations that have taken place over the past two decades. We argue that it is time to change the view that accountants' professional judgment is the application of accounting‐based knowledge and experience in the selection of an appropriate accounting method. Accountants now face a standard‐setting context that emphasizes the estimation of future cash flows as well as new business and financial realities. This context implies that, in exercising their professional judgment to choose between forecast alternatives, accountants must rely on knowledge and experience from other disciplines (even though this is not well integrated into accounting). Hence, accounting must evolve from its traditional stewardship role to the new role of “forecount‐ing” (the estimation of future cash flows). The implications as well as the challenges of that evolution are discussed.
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 | 0.014 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.010 | 0.042 |
| Scholarly communication | 0.019 | 0.008 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".