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Record W2614533353 · doi:10.7202/1034629ar

Promotion de la santé en milieu urbain : le Centre de prévention de Nyon

2016· article· fr· W2614533353 on OpenAlexvenueno aff
Philippe Lehmann, Yolande Dormond

Bibliographic record

VenueInternational Review of Community Development · 2016
Typearticle
Languagefr
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

Le Centre de Nyon (Suisse romande) est le produit d’un programme de recherche scientifique appliquée sur la prévention des maladies cardio-vasculaires. L’analyse des aspects les plus marquants, les conditions de cette expérimentation, l’évaluation qui en a été faite, les développements qu’elle a suscités ailleurs en Suisse romande permettent de montrer combien cette expérience associe une expérimentation scientifique, un projet d’animation en éducation communautaire, un contact étroit avec une clientèle toujours plus nombreuse et des projets politiques. Si le centre de Nyon devient progressivement un modèle de référence de l’idée d’une prévention dans la communauté, encore s’agit-il de s’interroger sur les pratiques de prévention au regard de deux modèles de référence : l’étude des modes de vie et des cultures au quotidien et le modèle de la politique de santé. Il résulte de cet examen que le centre de prévention est caractérisé par une recherche de gain individuel de bien-être et de liberté — un « égoïsme de la santé » — qui, s’il ne cherche pas à faire de la santé le bien privilégié d’une solidarité sociale, joue un rôle de valorisation, y compris des individus les moins privilégiés.

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)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.120
Threshold uncertainty score0.238

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.004
Scholarly communication0.0050.002
Open science0.0010.007
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0110.001

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 head0.094
GPT teacher head0.459
Teacher spread0.365 · 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 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

Citations0
Published2016
Admission routes1
Has abstractyes

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