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Record W4406384132 · doi:10.51926/iste.9781836120278

Une société plus inclusive pour les personnes dépendantes ou handicapées

2025· book· fr· W4406384132 on OpenAlexaboutno aff
Corinne Grenier, Elizabeth Franklin-Johnson, Giovany Cajaiba-Santana

Bibliographic record

Venuenot available
Typebook
Languagefr
FieldHealth Professions
TopicAging, Elder Care, and Social Issues
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyPolitical science

Abstract

fetched live from OpenAlex

Promouvoir une société plus inclusive pour les personnes âgées ou en situation de handicap, et plus largement toutes les personnes fragilisées, suppose de profondes transformations du système de santé dans de nombreux pays. Ce mouvement qualifié de « désinstitutionalisation » implique le renforcement de la participation des personnes aux décisions et aux activités qui les concernent, qu’elles vivent en établissement, dans leur milieu ordinaire, et dans le respect de leurs habitudes et de leurs projets de vie. Il s’agit alors de viser un objectif de participation sociale, en considérant les publics accompagnés comme des partenaires des organisations, véritables acteurs professionnels et institutionnels qui contribuent à cette transformation du système de santé. Cet ouvrage réunit les contributions de plus de 40 chercheurs de différents pays (francophones et canadiens notamment) ainsi que celles de patients engagés dans des recherches, des expérimentations ou des associations. Ces contributions examinent les fondements terminologiques et juridiques d’une société plus inclusive – les différents dispositifs, formes innovantes d’habitats et modalités d’accompagnement des publics et des professionnels en faveur de l’inclusion – et les différents modèles d’animation de territoires, favorisant l’engagement communautaire de tous en faveur de l’inclusion.

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)0.007
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 score0.023
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0110.009
Scholarly communication0.0070.006
Open science0.0010.011
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0190.003

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 head0.046
GPT teacher head0.399
Teacher spread0.353 · 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
Published2025
Admission routes1
Has abstractyes

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