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Record W3138362105

Culture sanitaire internationale : pour une rencontre des savoirs

2020· article· fr· W3138362105 on OpenAlexaff
Alexia Pilon Diabaté

Bibliographic record

VenueCommposite · 2020
Typearticle
Languagefr
FieldSocial Sciences
TopicAfrican Studies and Ethnography
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsHumanitiesPolitical scienceEthnologySociologyArt
DOInot available

Abstract

fetched live from OpenAlex

Les connaissances scientifiques produites dans le champ de la sante publique et mondiale sont souvent considerees comme objectives. Toutefois, elles comportent des jugements de valeur et participent a definir la sante de maniere normative, faisant fi du contexte social ou de l’environnement culturel dans lequel elles operent. Dans cet article, nous chercherons a mettre en lumiere comment la sante normative, definie dans le champ interdisciplinaire de la sante publique et mondiale, promeut une universalisation des prescriptions et proscriptions des comportements s’apparentant a de l’imperialisme culturel. A travers les resultats d’une etude de terrain realisee a Yopougon, commune de la ville d’Abidjan, en Cote d’Ivoire, nous identifierons certaines tensions entre des savoirs de ce que nous nommons la « culture sante internationale » et des savoirs populaires experientiels. Nous suggerons qu’il faille conjuguer les savoirs scientifiques et populaires pour guider les interventions sanitaires en Cote d’Ivoire, afin de permettre la collaboration entre des membres des domaines professionnels et scientifiques de la sante et les localites concernees. L’etude des representations sociales de la sante, comprises comme les croyances, les informations, les valeurs et les normes constitutives d’une societe, semble une avenue prometteuse pour reflechir les tensions entre la culture sante internationale et les savoirs populaires experientiels.

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)0.012
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.033
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0090.018
Scholarly communication0.0110.009
Open science0.0010.009
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0070.001

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 head0.061
GPT teacher head0.301
Teacher spread0.240 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2020
Admission routes1
Has abstractyes

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