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Record W1487107217 · doi:10.7202/044199ar

L’automédication

2010· article· fr· W1487107217 on OpenAlexvenueno aff
Sylvie Fainzang

Bibliographic record

VenueAnthropologie et Sociétés · 2010
Typearticle
Languagefr
FieldHealth Professions
TopicHealthcare Systems and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceDicationPhilosophyPhysics

Abstract

fetched live from OpenAlex

Aujourd’hui plus que jamais, la pratique de l’automédication fait l’objet d’une grande attention, tant des milieux professionnels de la santé que des sciences sociales. Non pas parce que la pratique serait nouvelle, mais parce qu’elle est nouvellement encouragée, en France, par les politiques publiques. À ce titre, il convient de s’interroger sur la question de savoir quelles sont, dans ce nouveau contexte, les motivations et les conditions de ce recours. On montrera ici, à partir d’enquêtes de terrain, que le recours à l’automédication ne se limite pas à soigner des pathologies bénignes, comme le préconisent les messages sanitaires, ou à répondre aux nouvelles mesures économiques qui accompagnent l’accès aux médicaments, mais correspond parfois aussi à une tentative de contournement des médecins généralistes, équivalant ainsi à une stratégie d’esquive.

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)0.008
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.055
Threshold uncertainty score0.184

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0040.004
Open science0.0010.004
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0550.020

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 head0.471
GPT teacher head0.718
Teacher spread0.246 · 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

Citations18
Published2010
Admission routes1
Has abstractyes

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