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Record W4413311103 · doi:10.7202/1119165ar

Trajectoire et vécu des aidantes et aidants lors de la crise sanitaire de la covid-19 en France

2025· article· fr· W4413311103 on OpenAlexvenueno aff
Christèle Meilland, Virginia Mellado, Arnaud Trenta

Bibliographic record

VenueLien social et Politiques · 2025
Typearticle
Languagefr
FieldHealth Professions
TopicHealthcare Systems and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)Political scienceSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakHumanitiesArtMedicineVirologyOutbreakInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

En France, la crise sanitaire du Covid-19 et le confinement généralisé de la population ont exercé une forte tension sur l’activité d’aide des proches de personnes âgées en perte d’autonomie et de personnes en situation de handicap. Les restrictions de déplacement et la fermeture de nombreux services sanitaires et médico-sociaux ont renforcé l’isolement des aidantes et des aidants qui accompagnent leur proche à domicile. Entre mars et mai 2020, une enquête par questionnaire a été menée en ligne auprès des adhérents des associations membres du Collectif Inter-Associatif des Aidants Familiaux (1032 réponses). L’article analyse les différents vécus de l’aide pendant le confinement en comparant les situations selon le genre de l’aidant et le lien avec la personne aidée. Il interroge également la relation entre la trajectoire d’aide et le vécu d’une crise aussi aigüe que la pandémie de Covid-19.

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)0.006
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: Empirical
Teacher disagreement score0.243
Threshold uncertainty score0.484

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.068
GPT teacher head0.534
Teacher spread0.466 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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