261.8: Organ donation following medical assistance in dying: A Canadian environmental scan.
Bibliographic record
Abstract
Background: Organ donation following MAiD presents intricate moral and ethical considerations, touching on societal norms, individual autonomy, and donation related experiences for all those involved. While this practice offers potential relief for organ shortages, its novelty demands tailored regulations and guidelines to ensure safety and ethical practice. As Canada leads in this domain, this environmental scan is an initiative from Canadian Blood Services aimed to elucidate the various elements of organ donation processes following MAiD in Canada. Methods: Multi-phased research approach where phase 1 involves updating a scoping review previously conducted by our research team on organ donation practices following MAiD worldwide. Phase 2 will employ a cross-sectional survey to gather insights from Organ Donation Organizations (ODOs) and healthcare professionals (HCPs) regarding current practices and challenges across Canada. Phase 3 will use a qualitative approach to interview Organ and Tissue Donation Coordinators (OTDCs) and MAiD providers to delve deeper into procedural details and experiences in Canada. Phase 4 will entail a retrospective data review to analyze organ donation statistics of MAiD patients across Canadian ODOs. Ethics: Research approval is being obtained at Brock University and all phases adhere to the Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans (TCPS 2), including obtaining informed consent and ensuring confidentiality. Implications and Dissemination: This environmental scan is currently being developed, and our findings will help inform policy change, clinical practice, and educational initiatives surrounding organ donation following MAiD across Canada. Results will be disseminated through peer-reviewed publications, conference presentations, and engagement with relevant stakeholders. This work is funded by Canadian Blood Services.
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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 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.018 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".