Assisted dying and palliative care in three jurisdictions: Flanders, Oregon, and Quebec
Bibliographic record
Abstract
BACKGROUND: An increasing number of jurisdictions around the world are legalizing assisted dying. This creates a particular challenge for the field of palliative care, which often precludes producing premature death by the injection or self-administration of lethal medications upon a patient's voluntary request. A 2019 systematic scoping review of the literature about the relationship between palliative care and assisted dying in contexts where assisted dying is lawful, found just 16 relevant studies that included varied and combined stances ranging from complete opposition, to collaboration and integration. Building on that review, the present study was conducted in Quebec (Canada), Flanders (Belgium), and Oregon (USA), with the objective of exploring the relationship between palliative care and assisted dying in these settings, from the perspective of clinicians and other professionals involved in the practice. METHODS: Semi-structured in-depth qualitative interviews were conducted with 29 professionals from Oregon [10], Quebec [9] and Flanders [10]. Participants were involved in the development of policy, management, or delivery of end of life care services in each of the jurisdictions. Data was analyzed thematically and followed a procedure of data immersion, and the construction of a thematic and interpretive account. RESULTS: Three themes were identified from each of the locations. Flanders: the integrated approach; discontents in palliative care; concerns about liberalization of assisted dying laws. Oregon: the role of hospice; non-standardized protocols and policies; concerns about access to medications and care. Quebec: a contested relationship; the special situation of independent hospice; lack of knowledge about and access to palliative care. CONCLUSIONS: No clear and uniform relationship between palliative care and assisted dying can be identified in any of the three locations. The context and practicalities of how assisted dying is being implemented alongside access to palliative care need to be considered to inform future laws. We seek a better understanding of whether and in what ways assisted dying presents a threat to palliative care.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".