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L’automédication chez les usagers de drogues : de la constitution de savoirs expérientiels à leur confrontation aux médecins

2019· article· fr· W2898319334 on OpenAlexaff
Lise Dassieu

Bibliographic record

VenueAnthropologie et santé · 2019
Typearticle
Languagefr
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

La dimension thérapeutique que peut revêtir la prise de drogues aux yeux des usagers reste peu explorée en sciences sociales. À partir d’une enquête qualitative, cet article étudie les pratiques d’automédication des usagers de drogues, ainsi que l’attitude des médecins généralistes à leur égard. La disponibilité des traitements de substitution aux opiacés sur le marché noir permet aux usagers de les utiliser en automédication pour soulager les symptômes de manque. Ces derniers consomment aussi divers médicaments et drogues illicites lorsqu’ils doivent faire face à des problèmes de santé courants (grippe, douleur, angoisse, par exemple). Par le biais de l’auto-expérimentation et de l’échange entre pairs, ils développent des savoirs expérientiels sur les produits et leur maniement, constitués et transmis au sein du monde des drogues. Mais ces savoirs ne sont pas toujours reconnus comme tels par les médecins, qui interprètent souvent l’automédication des usagers de drogues comme un mésusage ou une inobservance du traitement.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.358
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.005
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.074
GPT teacher head0.457
Teacher spread0.383 · 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; both teacher heads agree on what is shown here.

Study designObservational
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

Citations6
Published2019
Admission routes1
Has abstractyes

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