Physicians and euthanasia: a Canadian print-media discourse analysis of physician perspectives
Bibliographic record
Abstract
BACKGROUND: Recent events in Canada have mobilized public debate concerning the controversial issue of euthanasia. Physicians represent an essential stakeholder group with respect to the ethics and practice of euthanasia. Further, their opinions can hold sway with the public, and their public views about this issue may further reflect back upon the medical profession itself. METHODS: We conducted a discourse analysis of print media on physicians' perspectives about end-of-life care. Print media, in English and French, that appeared in Canadian newspapers from 2008 to 2012 were retrieved through a systematic database search. We analyzed the content of 285 articles either authored by a physician or directly referencing a physician's perspective. RESULTS: We identified 3 predominant discourses about physicians' public views toward euthanasia: 1) contentions about integrating euthanasia within the basic mission of medicine, 2) assertions about whether euthanasia can be distinguished from other end-of-life medical practices and 3) palliative care advocacy. INTERPRETATION: Our data showed that although some medical professional bodies appear to be supportive in the media of a movement toward the legalization of euthanasia, individual physicians are represented as mostly opposed. Professional physician organizations and the few physicians who have engaged with the media are de facto representing physicians in public contemporary debates on medical aid in dying, in general, and euthanasia, in particular. It is vital for physicians to be aware of this public debate, how they are being portrayed within it and its potential effects on impending changes to provincial and national policies.
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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 | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Qualitative | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Qualitative | medium |
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 | 0.011 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.019 | 0.024 |
| Science and technology studies | 0.016 | 0.011 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".