Unfinished Business: Ongoing Ethical Exceptionalism in the Oversight of Human Pluripotent Stem Cell Research in Canada
Bibliographic record
Abstract
In this article, we critically examine the arguments for and against the exceptional status given human pluripotent stem cell research in Canada (through the latest [December 2010] revision of the Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans), and conclude that this exceptionalism is unwarranted and ethically unsound. In our view, the three federal research granting agencies should honor their longstanding commitment that researchers, research sponsors, and Research Ethics Boards in Canada have access to "a single reference document for all research involving humans conducted under the auspices of institutions eligible for Agency funding." As well, responsibility for the development, interpretation, and implementation of Canada's research ethics guidelines should be under the authority of a single oversight body that is independent of the federal research granting Agencies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Metaresearch Domain: Methods · Genre: Empirical About the Canadian research system: yes · About a Canadian topic: yes | Theoretical or conceptual | low |
| gpt | MetaresearchScience and technology studies Domain: Methods · Genre: Commentary About the Canadian research system: yes · About a Canadian topic: yes | Theoretical or conceptual | high |
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 | 0.086 | 0.124 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.046 | 0.058 |
| Scholarly communication | 0.028 | 0.007 |
| Open science | 0.006 | 0.013 |
| Research integrity | 0.015 | 0.030 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".