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Record W2048831804 · doi:10.7202/043301ar

De l'aptitude à consentir à un traitement ou à le refuser : une analyse critique

2005· article· fr· W2048831804 on OpenAlexaffvenue
Danielle Blondeau, Éric Gagnon

Bibliographic record

VenueLes Cahiers de droit · 2005
Typearticle
Languagefr
FieldHealth Professions
TopicHealth, Medicine and Society
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPhilosophyHumanitiesAptitudePsychology

Abstract

fetched live from OpenAlex

L'évaluation de l'aptitude du patient à consentir à un traitement ou à le refuser constitue aujourd'hui la seule limite à l'exercice du droit de refuser un traitement. La notion d'aptitude sert par conséquent à préciser le contenu et l'étendue de l'autonomie d'une personne. En raison du rôle déterminant acquis par cette notion, des définitions en ont été proposées, de même que des tests et des critères pour l'évaluer. Les auteurs cherchent à montrer ce que ces définitions sous-entendent, sur quels choix et orientations reposent les critères d'évaluation, afin de comprendre quelles options ils excluent, quels présupposés sont admis, quels problèmes ils soulèvent. L'examen des origines et des transformations des critères et des tests d'aptitude les conduira à discuter des réductions que finit par subir la notion d'autonomie.

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)0.014
metaresearch head score (Gemma)0.053
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: none
Teacher disagreement score0.014
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.053
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0010.009
Scholarly communication0.0060.005
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.026
GPT teacher head0.365
Teacher spread0.339 · 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

Citations5
Published2005
Admission routes2
Has abstractyes

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