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Record W2102347680 · doi:10.7202/018816ar

Personnification et individualisation des corps malades : enjeu politique ou gestion individuelle dans la lutte contre le cancer du sein

2008· article· fr· W2102347680 on OpenAlexvenueno aff
Sandrine Knobé

Bibliographic record

VenueLien social et Politiques · 2008
Typearticle
Languagefr
FieldHealth Professions
TopicHealth, Medicine and Society
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

L’article s’attache à l’analyse des conceptions sociales et politiques du corps malade développées dans le contexte d’une association de lutte contre le cancer du sein mêlant entraide et militantisme, pour montrer que la lutte contre une certaine forme de dépossession du corps laisse apparaître des difficultés d’articulation entre enjeux politiques et intérêts individuels. La première partie est ainsi consacrée à la manière dont l’enjeu que représente la personnification des corps malades s’appréhende en termes politiques tout en renvoyant à des stratégies individuelles de lutte contre le pouvoir médical. La deuxième partie s’intéresse, quant à elle, à la question de l’individualisation des corps malades rendant difficile la désingularisation des expériences, mais servant sans doute de point d’appui à une construction sociale et politique du libre-choix.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.995
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.018
Scholarly communication0.0040.003
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.099
GPT teacher head0.411
Teacher spread0.312 · 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.

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
Published2008
Admission routes1
Has abstractyes

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