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Record W2058213990 · doi:10.3917/seve.042.0041

Roselyne Bachelot et la loi hpst

2014· article· fr· W2058213990 on OpenAlexaff
Éric Favereau

Bibliographic record

VenueLes Tribunes de la santé · 2014
Typearticle
Languagefr
FieldHealth Professions
TopicHealthcare Systems and Practices
Canadian institutionsWorld Federation of Science Journalists
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

La loi HPST est née sous le règne de Nicolas Sarkozy, c’est-à-dire à une époque où le conflit était valorisé, présenté comme le signe de la justesse et du courage de ceux qui le portaient. Ce fut donc logiquement un échec en termes de communication. Paradoxalement, l’échec de sa naissance n’a pas nui à sa survie. Agrémentée de quelques aménagements, elle s’est imposée ensuite et nul ne remet plus en cause les ARS comme la nouvelle gouvernance. Elle peut même rester comme une des dernières grandes lois hopistalières, car aujourd’hui l’enjeu n’est plus l’hôpital mais le parcours de soins.

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)0.003
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.044
Threshold uncertainty score0.146

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.004
Scholarly communication0.0060.004
Open science0.0010.003
Research integrity0.0030.008
Insufficient payload (model declined to judge)0.0440.012

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 head0.052
GPT teacher head0.499
Teacher spread0.447 · 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
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

Citations0
Published2014
Admission routes1
Has abstractyes

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