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Record W2901996803 · doi:10.1071/ah18172

Documenting the process of developing the Victorian voluntary assisted dying legislation

2018· article· en· W2901996803 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAustralian Health Review · 2018
Typearticle
Languageen
FieldPsychology
TopicGrief, Bereavement, and Mental Health
Canadian institutionsCarbon Engineering (Canada)
Fundersnot available
KeywordsLegislationPopulation healthGovernment (linguistics)Health economicsProcess (computing)Public healthBusinessMedicinePublic administrationPolitical scienceLawNursingComputer science

Abstract

fetched live from OpenAlex

Many countries across the world have legislated for their constituents to have control over their death. Commonalities and differences can be found in the regulations surrounding the shape and practices of voluntary assisted dying (VAD) and euthanasia, including an individual’s eligibility and access, role of health professions and the reporting. In Australia there have been perennial debates across the country to attempt legislative change in assisting a terminally ill person to control the ending of their life. In 2017, Victoria became the first state to successfully legislate for VAD. In describing the Victorian process that led to the passage of legislation for VAD, this paper examines the social change process. The particular focus of the paper is on the vital role played by a multidisciplinary ministerial advisory panel to develop recommendations for the successful legislation, and is written from their perspective. What is known about the topic? VAD has not been legal in an Australian state until legislation passed in Victoria in 2017. What does this paper add? This paper describes how the legislation was developed, as well as the significant consultative and democratic processes required to get the bill to parliament. What are the implications for practitioners? In documenting this process, policy makers and others will have an understanding of the complexities in developing legislation. This information will be useful for other Australian jurisdictions considering similar legislative changes.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.722
Threshold uncertainty score0.557

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.118
GPT teacher head0.454
Teacher spread0.336 · 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