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Record W2377371691 · doi:10.7202/1039117ar

Le nouveau management public comme prémisse aux transformations des systèmes de santé nationalisés : les cas du Québec et du Royaume-Uni

2017· article· fr· W2377371691 on OpenAlexvenueaboutno aff
Mélanie Bourque

Bibliographic record

VenueRevue Gouvernance · 2017
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesPublic managementArt

Abstract

fetched live from OpenAlex

Les systèmes de santé font l’objet du débat politique depuis les années 1990. Ces débats, qui portent sur le vieillissement de la population, l’évolution technologique et les demandes accrues des usagers, ont amené la plupart des pays occidentaux à réformer leur système. Malgré les orientations différentes qu’ont pris les réformes, les transformations des systèmes de santé nationalisé, mandaté et entrepreneurial ont principalement visé la réduction des coûts. Cet article tente de montrer que l’application des principes du nouveau management public aux systèmes de santé du Québec et du Royaume-Uni s’est principalement faite dans le but de contourner les contraintes que sont : l’universalité, le financement public et l’unicité de gestion. Ces caractéristiques fondamentales des systèmes nationalisés ont conduit les décideurs à créer un « marché intérieur » qui vise la mise en concurrence des établissements de santé les uns par rapport aux autres en ayant pour objectif principal l’atteinte des résultats préalablement fixés. L’application du nouveau management public transforme les fondements des systèmes de santé du Québec et du Royaume-Uni, et par le fait même, remet en question leur catégorisation en tant que système nationalisé.

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)0.006
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.917
Threshold uncertainty score0.600

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0080.006
Scholarly communication0.0080.003
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0110.001

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 head0.049
GPT teacher head0.316
Teacher spread0.267 · 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 designQualitative
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

Citations13
Published2017
Admission routes2
Has abstractyes

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