The Life and Death of the Canadian Contingent Gains and Losses Accounting Standards Project*
Bibliographic record
Abstract
ABSTRACT In April 1994, the Canadian Accounting Standards Board formally approved a new accounting standard for contingent gains and losses. The new standard would have increased the frequency of recording contingent losses, enabled the accrual of some contingent gains, and enhanced disclosures for all contingencies. The changes would primarily have been achieved by requiring management, and their legal advisers, to make predictions, estimates, and disclosures that the existing accounting standard enabled them to avoid. Over two years later, and following numerous changes to the implementation date, the board ultimately decided not to release the new standard, and in July 1999, formally abandoned the contingencies project. This study provides a telling of the standard's genesis, development, and ultimate demise, which should prove instructive to those parties with an interest and a stake in accounting standard setting.
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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 | 0.022 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.029 | 0.012 |
| Scholarly communication | 0.015 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".