MétaCan
Menu
Back to cohort

Éditorial : De la croissance des dépenses à la croissance de la productivité dans le secteur de la santé

2013· book-chapter· fr· W1504208829 on OpenAlexaboutno aff
Stéfano Scarpetta

Bibliographic record

VenuePanorama de la santé · 2013
Typebook-chapter
Languagefr
FieldHealth Professions
TopicHealthcare Systems and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

Près de six ans après le début de la crise financière et économique mondiale, la situation économique est très variable selon les pays de l’OCDE, entre l’amorce d’une reprise aux États-Unis, au Canada et au Japon, et des perspectives toujours moroses dans de nombreux pays européens. Après une période où, dans le cadre des plans de relance, des ressources importantes ont été allouées aux programmes de protection sociale, le retour à des mesures visant à rétablir l’équilibre budgétaire se traduit souvent par des coupes sombres dans les dépenses. À l’image d’autres postes de dépenses publiques, le secteur de la santé subit aussi des restrictions budgétaires dans de nombreux pays de l’OCDE.

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)0.002
metaresearch head score (Gemma)0.008
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: Editorial · Consensus signal: Editorial
Teacher disagreement score0.022
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0020.002
Scholarly communication0.0040.004
Open science0.0010.001
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0220.012

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 head0.035
GPT teacher head0.414
Teacher spread0.378 · 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
GenreEditorial

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
Published2013
Admission routes1
Has abstractyes

Explore more

Same venuePanorama de la santéSame topicHealthcare Systems and PracticesFrench-language works237,207