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Record W3122450675

Final Report of the Royal Society of Canada Expert Panel: End-of-Life Decision-Making

2011· article· en· W3122450675 on OpenAlexaboutno aff
Jocelyn Downie

Bibliographic record

VenueKnowledge@SchulichLaw · 2011
Typearticle
Languageen
FieldHealth Professions
TopicMedical Malpractice and Liability Issues
Canadian institutionsnot available
Fundersnot available
KeywordsHealth careOccupational safety and healthPublic relationsScale (ratio)Political scienceBusinessEconomic growthMedicinePublic administrationLawEconomicsGeography
DOInot available

Abstract

fetched live from OpenAlex

Patient safety has become a significant and pressing policy issue. Around the world, governments, the health care sector and the public are increasingly cognizant of the need to improve the safety of care delivered by their health systems. Pressure for change has been created by highly publicized incidents in a number of countries involving unsafe acts that were significant both in scale and consequence and a number of empirical studies that revealed the high rates of unsafe acts and their consequences. The costs of unsafe health care – both personal and fiscal – to individuals, their families and their communities and to the state are massive. In this research project we explored one particular avenue for change – that is, the use of legal instruments by governments to improve patient safety. We did this through a comparative review of the use of legal instruments or frameworks in other countries (specifically Australia, Denmark, New Zealand, the United Kingdom, and the United States) as well as two non-health care related sectors in Canada (transportation and occupational health and safety). We began this research by reviewing the legal instruments and undertaking extensive literature reviews. Further information was gathered through in-person interviews with policy-makers and academics in the countries studied, and from policy-makers and academics expert in the health, occupational health and safety, and transportation sectors in Canada. Once descriptions of the various countries and sectors were drafted, we held small-group meetings with local experts on particular aspects of patient safety. We then hosted a national consultation meeting. We subsequently drafted this final report and the appendices, which fully describe the results of the background research. Finally, we prepared a summary version of the report as well as posters and papers to be published and delivered at conferences and meetings with relevant groups. co-authors: Udo Schuklenk, Johannes J.M. Van Delden, Sheila McLean, Ross Upshur, Daniel Marc Weinstock

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)0.002
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.195
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.141
GPT teacher head0.416
Teacher spread0.275 · 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 designNot applicable
Domainnot available
GenreEmpirical

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

Citations0
Published2011
Admission routes1
Has abstractyes

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