Bibliographic record
Abstract
Carter v Canada (Attorney General) is a Canadian case that famously struck down the Canadian Criminal Code prohibitions on euthanasia and assisted suicide (now known collectively as medical assistance in dying or MAiD). The most significant issue in the Carter case was that of the status of MAiD. However, this case is also interesting to explore in relation to the issue of the use of expert evidence from social science and humanities researchers. In this paper, I offer reflections as an academic trained in philosophy and law but not expert in the use of social science and humanities evidence in litigation. As someone who was inside the litigation but outside the generation of the evidence, I seek to bring a perspective that may be useful to practitioners who might be thinking about working with academics and academics who might be thinking about getting involved in constitutional litigation that relates to their field of study.
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
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 | 0.044 | 0.100 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.029 | 0.043 |
| Scholarly communication | 0.022 | 0.011 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.020 | 0.017 |
| Insufficient payload (model declined to judge) | 0.004 | 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, 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".