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Record W2142861177 · doi:10.1016/j.alter.2011.08.001

Définir l’aide humaine en France

2011· article· fr· W2142861177 on OpenAlexaff
Virginie Scolan, Frédérique Fiechter-Boulvard, Jean‐Yves Salle

Bibliographic record

VenueAlter · 2011
Typearticle
Languagefr
FieldHealth Professions
TopicAging, Elder Care, and Social Issues
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsHumanitiesPolitical scienceEthnologySociologyPhilosophy

Abstract

fetched live from OpenAlex

En France, plus de 760 000 personnes en situation de handicap sollicitent une ou plusieurs aides humaines professionnelles ou non professionnelles avec une prépondérance pour les aidants familiaux. Leur présence auprès des personnes en situation de handicap est indispensable à leur vie. Les aidants apparaissent pluriels et les définir peut s’avérer délicat. En effet, quel que soit le cadre sociojuridique de la sollicitation de l’aide humaine, la notion d’aidant revêt à la fois un caractère financier et un caractère humain, c’est-à-dire la personne d’aidant elle-même. Compte tenu des enjeux humains et financiers pouvant alors restreindre leur présence, il nous est apparu nécessaire de définir au mieux cet aidant en s’intéressant plus particulièrement à sa définition en droit social et en droit du dommage corporel.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.285
Threshold uncertainty score0.567

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0030.003
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.076
GPT teacher head0.375
Teacher spread0.299 · 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 designQualitative
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
Published2011
Admission routes1
Has abstractyes

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