An Interprofessional Interpretation of Ontario’s CPSO End-of-Life Policy
Bibliographic record
Abstract
In the acute care setting, we often ask families to make challenging decisions regarding their loved ones’ preferences and choices for end-of-life care when these individuals can no longer make those decisions themselves. This already stressful situation can be exacerbated by medical jargon and conflicting messaging from various well-meaning health care practitioners. Some of this ambiguity likely stems from medical providers’ lack of familiarity with end-of-life policies and their obligations as providers. Further, there can be discomfort for many families and clinicians about speaking about end of life, alongside varying cultural norms and expectations around death and dying. In this analysis, we aim to outline fundamental concepts and misconceptions surrounding cardiopulmonary resuscitation, the administration and withdrawal of life-sustaining therapies, and the framework provided by regulatory bodies for medical professionals to approach these situations. As legal and ethical principles may vary nationally between jurisdictions, our discussion will be based on Ontario policy and law. However, we believe that a similar approach would help hospitals and health care bodies provide clarity to clinicians, patients and families alike, and could be easily adapted into medical education materials.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".