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Medical assistance in dying in rural communities: A review of Canadian policies and guidelines

2022· review· en· W4296674292 on OpenAlexafffundabout
Alessandro Manduca-Barone, Julia Brassolotto, Duff Waring

Bibliographic record

VenueJournal of Rural Studies · 2022
Typereview
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsYork UniversityUniversity of Lethbridge
FundersSocial Sciences and Humanities Research Council of CanadaAlberta Innovates
KeywordsRuralityLegislationScholarshipParliamentPolitical sciencePublic administrationRural areaEconomic growthPublic relationsMedicinePoliticsLaw

Abstract

fetched live from OpenAlex

In June 2016, the Canadian Parliament passed Bill C-14, legalizing medical assistance in dying (MAiD), elsewhere known as voluntary euthanasia or physician-assisted suicide. Related legislation and policies continue to evolve. However, there is a paucity of scholarship regarding their distinct implications for rural communities. This is significant given that rurality is an underrecognized but important determinant of health. In order to address this gap, we conducted a rural-focused scan of policies, guidelines, and legislation that govern the practice of MAiD in Alberta, Canada (N = 16). Drawing from rural health scholarship, we reviewed these documents with a focus on three key rural considerations (place, community, and relationships) and identified potential implications. Through an analysis of these findings, we identified four opportunities where policy can better serve rural communities. These included addressing geographic location, continuity of care, dual relationships, and systemic barriers. In light of this, we offer several recommendations for how future policy and guidelines can better support rural residents.

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.542
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.343
GPT teacher head0.573
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations10
Published2022
Admission routes3
Has abstractyes

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