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Record W2774802509 · doi:10.7202/1038634ar

Mourir comme mode de vie

2017· article· fr· W2774802509 on OpenAlexaffvenue
Ari Gandsman, T. Elijah Herington, Antoine Przybylak‐Brouillard, Anne-Hélène Kerbiriou

Bibliographic record

VenueAnthropologie et Sociétés · 2017
Typearticle
Languagefr
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsHumanitiesPhilosophyPolitical science

Abstract

fetched live from OpenAlex

On considère que le droit de mourir, en tant que mouvement social contemporain d’importance, s’est constitué en réaction aux interventions biomédicales préoccupantes qui cherchent à prolonger la vie à tout prix. Cependant, l’aide médicale à mourir est elle aussi une intervention biomédicale reposant sur des technologies biomédicales et qui se fonde sur le langage de la technique biomédicale. Bien que les partisans du droit de mourir aient souvent recours à ce langage dans l’énoncé de leurs arguments, une écoute attentive des voix de ces activistes permet de nuancer et d’affiner l’approche des aspects contradictoires et multiples de cette expérience. La façon dont ils parlent de la mort révèle des préoccupations implicites se rapprochant davantage des notions heideggériennes de « l’art » et un prolongement des anciennes conceptions de « l’art de mourir ». Acceptant l’inéluctabilité de la mort, ou de vivre de façon àêtre vers la mort, les activistes se soucient souvent bien davantage de l’art de vivre et de mourir que de technique biomédicale.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.018
Scholarly communication0.0060.005
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0100.002

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 head0.309
GPT teacher head0.611
Teacher spread0.302 · 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 designQualitative
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

Citations1
Published2017
Admission routes2
Has abstractyes

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