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Record W2171520279 · doi:10.1136/qshc.2004.011510

Paradoxes of French accreditation

2005· article· en· W2171520279 on OpenAlexaff
MP. Pomey

Bibliographic record

VenueBMJ Quality & Safety · 2005
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Quality and Management
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsAccreditationGovernment (linguistics)Agency (philosophy)Health careBusinessQuality (philosophy)Public relationsHospital accreditationCertification and AccreditationPublic administrationMedicinePolitical scienceMedical educationLawSociology

Abstract

fetched live from OpenAlex

The accreditation system introduced into the French healthcare system in 1996 has five particular characteristics: (1) it is mandatory for all healthcare establishments; (2) it is performed by an independent government agency; (3) surveyors have to report all instances of non-compliance with safety regulations; (4) the accreditation report is delivered to regional administrative authorities and a summary is made available to the public; and (5) regional administrative authorities can use the information contained in the accreditation report to revise hospital budgets. These give rise to a number of paradoxes: (1) the fact that accreditation is mandatory lends itself to ambiguity and likens the process to an inspection; (2) the fact that decision makers can use the information contained in the accreditation report for resource allocation can incite establishments to adopt strategic behaviours aimed merely at complying with the accreditation manual; and (3) there is a tendency for establishments to reduce quality processes to nothing more than the completion of accreditation and to focus efforts on standardizing practices and resolving safety issues to the detriment of organizational development. All accreditation systems must be aware of these paradoxes and decide on the level of government involvement and the relationship between accreditation and resource allocation. With time, accreditation in France could benefit from both a professionally driven system and from the increased amount of freedom to focus on quality improvement which is necessary for organizational development.

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)0.064
metaresearch head score (Gemma)0.144
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: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.183
Threshold uncertainty score0.379

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0640.144
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.004
Science and technology studies0.0140.024
Scholarly communication0.0140.009
Open science0.0020.008
Research integrity0.0120.008
Insufficient payload (model declined to judge)0.0070.001

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 head0.216
GPT teacher head0.566
Teacher spread0.350 · 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

Citations67
Published2005
Admission routes1
Has abstractyes

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