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Record W4408159710 · doi:10.1515/9782763718286

Patient et citoyen

2014· book· fr· W4408159710 on OpenAlexaboutno aff
Nortin Hadler, Fernand Turcotte

Bibliographic record

Venuenot available
Typebook
Languagefr
FieldHealth Professions
TopicHealth, Medicine and Society
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

Dans ce nouvel ouvrage, Nortin Hadler remet en question le système de santé américain, mais son analyse vaut tout aussi bien pour le système de santé québécois. Les conflits d’intérêts, les fausses déclarations des essais cliniques, les dépenses massives pour des procédures d’efficacité douteuse - cela et d’autres failles critiques - laissent peu de doute sur une nécessaire refonte du système de santé actuel. Dans cet ouvrage essentiel, un médecin éminent, Nortin Hadler, exhorte les patients à envisager ce que pourrait être une réforme réussie des systèmes de santé qui mettrait de l’avant la relation entre le médecin et le patient. Portant un regard critique sur le traitement médical et le financement de la santé, le Dr Hadler utilise la richesse de son expérience et son analyse perspicace pour éclairer les citoyens, les patients et les décideurs politiques. L’auteur invite les patients citoyens à reprendre en main la souveraineté qui leur appartient en ce qui concerne toutes les décisions susceptibles d’affecter leur bien-être. Par l'auteur de Malades d’inquiétude? Diagnostic: la surmédicalisation ! et de Repenser le vieillissement. Recensions [[http://www.ledevoir.com/non-classe/429648/notre-systeme-de-sante-aux-soins-intensifs|Notre système de santé aux soins intensifs, article de Josée Blanchette, Le Devoir, janvier 2015]]

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)0.018
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: Other · Consensus signal: none
Teacher disagreement score0.029
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0290.004

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 head0.058
GPT teacher head0.412
Teacher spread0.353 · 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
GenreOther

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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