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Record W3204791858 · doi:10.3917/gs1.165.0263

Un dispositif Ehpad « hors les murs » : l’utilisation par ses bénéficiaires

2021· article· fr· W3204791858 on OpenAlexaff
Louis Braverman, Sandrine Dufour-Kippelen, Béatrice Fermon

Bibliographic record

VenueGérontologie et société · 2021
Typearticle
Languagefr
FieldHealth Professions
TopicAging, Elder Care, and Social Issues
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Favoriser le maintien à domicile de personnes âgées en perte d’autonomie conduit à développer de nouvelles organisations de prises en charge. Dans cet article, on s’intéresse à un dispositif expérimental d’Ehpad « hors les murs » qui offre une palette de services au sein d’un Ehpad ou au domicile pour un accompagnement renforcé au domicile. L’adéquation des réponses offertes aux besoins exprimés par les aînés est un enjeu fort de ce type d’innovation. Les données collectées et les entretiens réalisés dans le cadre de l’évaluation de cette expérimentation permettent d’étudier les usages et les ressentis des bénéficiaires. Si les bénéficiaires et leurs aidants se déclarent globalement satisfaits de la personnalisation possible de l’accompagnement, des contraintes organisationnelles en limitent cependant l’étendue. Par ailleurs, le recours aux différents services proposés se caractérise par d’importantes variations, certaines prestations étant peu utilisées, voire jamais, alors que d’autres le sont régulièrement et par une proportion importante de bénéficiaires. Ces résultats alimentent le débat sur les limites du processus de désinstitutionnalisation que ces expérimentations visent.

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)0.007
metaresearch head score (Gemma)0.020
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 score0.019
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.020
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0190.002

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 head0.081
GPT teacher head0.421
Teacher spread0.341 · 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

Citations4
Published2021
Admission routes1
Has abstractyes

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