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Record W4399436683 · doi:10.1111/capa.12569

Quality Improvement Support Agencies as a systemic quality strategy: France and Québec

2024· article· en· W4399436683 on OpenAlexaffabout
Labanté Outcha Daré, François Champagne, Jean‐Louis Denis

Bibliographic record

VenueCanadian Public Administration · 2024
Typearticle
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsCentre Hospitalier de l’Université de MontréalUniversité de Montréal
Fundersnot available
KeywordsExcellenceQuality (philosophy)Consistency (knowledge bases)Quality managementBusinessSystemic riskPolitical sciencePublic administrationService (business)Computer scienceMarketingEconomics

Abstract

fetched live from OpenAlex

Abstract In a high‐quality health and social services system, policymakers encourage action at all levels of change to ensure the consistency of quality strategies. This is especially important at the systemic level, in which the other three levels of change are nested. This study aims to present an analysis of Quality Improvement Support Agencies as a systemic strategy, which has been successfully implemented in several jurisdictions. A comparative study of two critical cases in different jurisdictions was carried out: Haute autorité de santé in France (HAS) and Institut national d'excellence en santé et services sociaux (INESSS) in Québec, Canada.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.833
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.199
GPT teacher head0.478
Teacher spread0.278 · 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

Citations1
Published2024
Admission routes2
Has abstractyes

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