Bibliographic record
Abstract
On May 2-3, 2008, the Alberta School of Business and the Institute of Chartered Accountants of Alberta (ICAA) sponsored a dinner and a one-day research workshop in Professor Michael Gibbins's honor. At the dinner on May 2, three presentations were made on the contribution of Professor Gibbins to accounting education, research, and the profession. At the research workshop on May 3, three research papers were presented, a panel discussed professional judgment issues in accounting and auditing, and a CFO gave a luncheon speech on the new financial presentation project of the Financial Accounting Standards Board. The dinner and symposium attracted participants from across Canada, the United States, Australia, and Singapore, which is not surprising given Professor Gibbins's global reputation. This paper summarizes the presentations and discussion that took place during the May 2 dinner and May 3 research workshop.
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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 | 0.006 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.011 | 0.024 |
| Insufficient payload (model declined to judge) | 0.071 | 0.048 |
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".