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Record W7159655705 · doi:10.7202/1124568ar

Le don d’organes en contexte d’aide médicale à mourir : une analyse critique des discours dans la presse écrite québécoise francophone (2016-2024)

2025· article· fr· W7159655705 on OpenAlexaffvenueabout
Alexandra Guité‐Verret, Deborah Ummel, Mélanie Vachon, Émilie Lessard

Bibliographic record

VenueFrontières · 2025
Typearticle
Languagefr
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsUniversité de SherbrookeCégep de Rivière-du-LoupUniversité du Québec à Montréal
Fundersnot available
KeywordsContext (archaeology)PoliticsEthnographyPower (physics)

Abstract

fetched live from OpenAlex

Le don d’organes en contexte d’aide médicale à mourir est un phénomène rare, mais en augmentation depuis l’encadrement législatif des soins de fin de vie au Québec. Dans cet article, nous proposons une analyse des discours médiatiques sur le sujet, en nous concentrant sur la presse écrite québécoise francophone. Un total de 152 articles, publiés entre janvier 2016 et décembre 2024, ont été sélectionnés. Notre analyse fait ressortir cinq thèmes que nous décrivons de manière à mieux comprendre les représentations de ce nouveau phénomène : 1) propulser le don d’organes par l’aide médicale à mourir; 2) tenter d’isoler deux phénomènes pourtant liés; 3) transmettre et sauver la vie; 4) transformer la mort en vie; 5) lutter contre les obstacles au don. Nous interprétons ces thèmes de manière à éclairer certaines attitudes, valeurs et métaphores qui sous-tendent les discours dominants et qui proposent au public certains rapports au corps et au mourir.

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)0.005
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.180
Threshold uncertainty score0.361

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0190.024
Scholarly communication0.0100.004
Open science0.0010.003
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0080.001

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 head0.005
GPT teacher head0.259
Teacher spread0.253 · 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

Citations0
Published2025
Admission routes3
Has abstractyes

Explore more

Same venueFrontièresSame topicOrgan Donation and TransplantationFrench-language works237,207