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Record W2062665511 · doi:10.12927/hcpap.2011.22554

Responsibility for Canada's Healthcare Quality Agenda: Interviews with Canadian Health Leaders

2011· article· en· W2062665511 on OpenAlexaffvenueabout
Terrence Sullivan, Fredrick D. Ashbury, Jason Pun, Barbara Pitt, Nina Stipich, Jasmine Neeson

Bibliographic record

VenueA Nudge Too Far? A Nudge at All? On Paying People to Be Healthy · 2011
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Quality and Management
Canadian institutionsPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsScrutinyExcellenceQuality (philosophy)Health careLegislationPublic administrationPolitical sciencePublic relationsLaw

Abstract

fetched live from OpenAlex

Canadian healthcare is under increased scrutiny to improve quality and performance, and for good reason. The proliferation of provincial-level quality councils underscores the urgency to establish an aligned national quality agenda. Patient safety has long been held as a critical element of a high-quality healthcare system; with the inexorable growth in spending, efficiency has more recently been introduced. Efficiency and quality are both factors in Ontario's Excellent Care for All legislation introduced in June of 2010, and Quebec's l'Institut national d'excellence en santé et en services sociaux (INESSS) arising from the Castonguay report. These associations of quality and efficiency are also echoed in the US, Australian and UK public debates. The development of a quality agenda has concurrently precipitated discussion regarding responsibility for quality, particularly but not exclusively with the emergence of quality issues in the technical and interpretive pathology arena. The discussion and debate on responsibility have become preoccupations at the national, provincial, institutional and individual profession levels.

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)0.012
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
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 score0.084
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0040.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
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 head0.443
GPT teacher head0.486
Teacher spread0.043 · 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
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

Citations6
Published2011
Admission routes3
Has abstractyes

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