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Le décodage biologique. Diffusion d’une nouvelle médecine non-conventionnelle contre le cancer

2011· article· fr· W1574120754 on OpenAlexaff
Aline Sarradon‐Eck, Coralie Caudullo

Bibliographic record

VenueAnthropologie et santé · 2011
Typearticle
Languagefr
FieldMedicine
TopicHistorical and Scientific Studies
Canadian institutionsCentre de Santé et de Services Sociaux Cavendish
Fundersnot available
KeywordsHumanitiesPhilosophyPolitical science

Abstract

fetched live from OpenAlex

De nouvelles médecines alternatives, regroupées sous l’appellation « décodage biologique », reposent sur une conception psychosomatique du cancer. Elles sont apparues en Europe dans les années 1990. Dans une perspective critique, l’article tente de comprendre la diffusion de ces nouvelles thérapies. S’inspirant du travail de D. Fassin sur les réseaux de l’ethnopsychiatrie, il analyse la construction d’une légitimation du décodage biologique et de ses praticiens, en décrivant les réseaux qui diffusent les théories et favorisent l’adoption de la pratique. L’article montre l’enracinement de ces nouvelles thérapies dans des représentations sociales et des modèles culturels de l’étiologie du cancer et du “faire face” à la maladie qui permettent ou renforcent l’adoption et l’appropriation de la pensée psychosomatique alternative.

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)0.006
metaresearch head score (Gemma)0.012
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 score0.011
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.018
Scholarly communication0.0030.003
Open science0.0010.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.077
GPT teacher head0.365
Teacher spread0.288 · 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
Published2011
Admission routes1
Has abstractyes

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