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Record W2923483360 · doi:10.1136/bmj.l1340

RCP adopts neutral stance on assisted dying after poll of members

2019· article· en· W2923483360 on OpenAlexaboutno aff
Gareth Iacobucci

Bibliographic record

VenueBMJ · 2019
Typearticle
Languageen
FieldHealth Professions
TopicHealth Services Management and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsOpposition (politics)Quarter (Canadian coin)Opinion pollPollingPolitical sciencePosition (finance)PsychologyLawMedicineHistoryPublic opinionEconomics

Abstract

fetched live from OpenAlex

The Royal College of Physicians is to remove its opposition to assisted dying and adopt a neutral stance on the issue after announcing the results of a poll of its members. Of the 6885 doctors who responded to the poll (20% of the RCP’s members and fellows), 43% thought that the college should be opposed to changing the law on assisted dying. This was similar to the 44% when RCP members were last polled in 2014. But the proportion of respondents wanting the RCP to support a change in the law increased to 32% in 2019, from 25% in 2014. A quarter of respondents (25%) in the latest poll thought that the RCP should be neutral, down from 31% in 2014. The result means that the college will now adopt a neutral position, which it had pledged to …

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 imitation

Not 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.

metaresearch head score (Codex)0.052
metaresearch head score (Gemma)0.176
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.052
Threshold uncertainty score0.274

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0520.176
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0070.005
Scholarly communication0.0080.005
Open science0.0010.005
Research integrity0.0100.012
Insufficient payload (model declined to judge)0.0100.005

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 head0.075
GPT teacher head0.459
Teacher spread0.384 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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

Citations14
Published2019
Admission routes1
Has abstractyes

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