SCIENCE FICTION: A PROUD MOMENT IN TIME FOR CANADIAN BIOETHICS
Bibliographic record
Abstract
All Canadian bioethicists need to reflect on the meaning and value of their work, to see more clearly how the ethics of bioethics is being undermined from within. In the case involving Dr Olivieri, the Hospital for Sick Children, the University of Toronto, and Apotex Inc, there were countless opportunities for bioethical heroism. And yet, no bioethics heroes emerged from this case. Much has been written about the hospital’s and the university’s failures in this case. But what about the deafening silence from the Canadian bioethics community? Given the duty of bioethicists to ‘‘speak truth to power’’, this silence is troubling. To date, nothing has been written about the silence. This article is intended as a partial remedy. As well, the article pays tribute to heretofore unsung heroes among
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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 | 0.015 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.075 | 0.085 |
| Scholarly communication | 0.027 | 0.012 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.016 | 0.026 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".