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Record W2092425792 · doi:10.3917/rce.002.0206

Évaluer les services publics : l'exemple de la santé

2007· article· fr· W2092425792 on OpenAlexaff
Stéphane Le Bouler

Bibliographic record

VenueRegards croisés sur l'économie/Regards croisés sur l'économie · 2007
Typearticle
Languagefr
FieldHealth Professions
TopicHealthcare Systems and Practices
Canadian institutionsMusée de la Civilisation
Fundersnot available
KeywordsPolitical scienceHumanitiesCentralisationPhilosophy

Abstract

fetched live from OpenAlex

L'évaluation des actions établies dans l'intérêt de la santé des populations est chose récente en France. Après avoir passé en revue ce qu'il en est de l'évaluation aujourd'hui, Stéphane Le Bouler, responsable de la mission recherche de la DREES, souligne les prérequis d'une telle entreprise : rompre avec l'hypothèse de bienveillance sans dresser de nouvelles icônes, oser la concurrence par comparaison, développer une approche qualité véritable, prendre en compte la décentralisation. La mise en place d'une véritable « démocratie sanitaire » ne saurait ainsi se réduire à des formules de participation erratiques.

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)0.025
metaresearch head score (Gemma)0.024
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 score0.064
Threshold uncertainty score0.135

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.024
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0080.012
Scholarly communication0.0150.009
Open science0.0010.008
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0090.001

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 head0.409
Teacher spread0.360 · 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

Citations2
Published2007
Admission routes1
Has abstractyes

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