Bibliographic record
Abstract
ABSTRACT Ross Skinner built his intimate knowledge of the intricacies of the art of accounting through a very long and rich career as an “accounting philosopher". This allowed him to both observe, and be part of, the formalization of today's GAAP. The duration and timing of Skinner's career also allowed him to experience directly the gradual evolution of our accounting model from an approach based largely on principles to one based increasingly on rules. The objective of this paper is to look behind accounting figures, which are the product of varying combinations of rules and judgment, and to discuss some recent events that have rocked the auditing and accounting profession. Our comments are presented in the context of views expressed by Skinner in his 1995 “Judgment in Jeopardy” article. Skinner had a keen interest in accounting history. Therefore, we begin our paper by referring to Paciol's notion of “venture accounting". We use this notion to introduce our discussion of financial reporting, which has become an important instrument of resource allocation and a challenge for professional judgment. This leads us to describe some of the ideas Skinner presented in his article on accounting judgment as “visionary". Had we listened to him, perhaps we could have avoided some of the costly changes and additions recently imposed on our governance system, such as the creation of the Canadian Public Accountability Board and the tightening of several laws and regulations.
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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 | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.028 | 0.007 |
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".