Bibliographic record
Abstract
The Olivieri symposium offers an opportunity to reflect on the Canadian regulatory climate and public governance. Baylis’s paper raises a concern about the Canadian bio-ethics community’s collective silence and stewardship regarding the Olivieri case.1 A similar collective silence greeted the recent McDonald report2 on research governance in Canada. The McDonald report assessed the integrity and effectiveness of research governance arrangements and concluded that serious reform was required. Curiously, although the McDonald report was recently referred to in a Canadian Medical Association Journal (CMAJ) editorial as an example of Canadian leadership,3 it has never received an editorial commentary in the CMAJ. Nor has any article in the CMAJ ever addressed the McDonald report. Yet the CMAJ created an ethics editorship and a senior Canadian bioethicist was chosen for the position in light of the growing importance of ethics in public policy.4 A chapter of the McDonald report also focused on the mandate of the Canadian Medical …
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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 | 0.010 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.020 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.042 | 0.057 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".