Canadian French and English newspapers’ portrayals of physicians’ role and medical assistance in dying (MAiD) from 1972 to 2016: a qualitative textual analysis
Bibliographic record
Abstract
OBJECTIVE: To examine how Canadian newspapers portrayed physicians' role and medical assistance in dying (MAiD). DESIGN: Qualitative textual analysis. SETTING: Online and print articles from Canadian French and English newspapers. PARTICIPANTS: 813 newspaper articles published from 1972 to 2016. RESULTS: Key Canadian events defined five eras. From 1972 to 1990, newspapers portrayed physician's MAiD role as a social issue by reporting supportive public opinion polls and revealing it was already occurring in secret. From 1991 to 1995, newspapers discussed legal aspects of physicians' MAiD role including Rodriguez' Supreme Court of Canada appeal and Federal government Bills. From 1996 to 2004, journalists discussed professional aspects of physicians' MAiD role and the growing split between palliative care and physicians who supported MAiD. They also reported on court cases against Canadian physicians, Dr Kevorkian and suffering patients who could not receive MAiD. From 2005 to 2013, newspapers described political aspects including the tabling of MAiD legislation to change physicians' role. Lastly, from 2014 to 2016, newspapers again portrayed legal aspects of physicians' role as the Supreme Court of Canada was anticipated to legalise MAiD and the Québec government passed its own legislation. Remarkably, newspapers kept attention to MAiD over 44 years before it became legal. Articles generally reflected Canadians' acceptance of MAiD and physicians were typically portrayed as opposing it, but not all did. CONCLUSIONS: Newspaper portrayals of physicians' MAiD role discussed public opinion, politicians' activities and professional and legal aspects. Portrayals followed the issue-attention cycle through three of five stages: 1) preproblem, 2) alarmed discovery and euphoric enthusiasm and 3) realising the cost of significant progress.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.009 | 0.013 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".