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Record W2921075832 · doi:10.3917/eres.meida.2019.01

Figures du vieillir et formes de déprise

2019· book· fr· W2921075832 on OpenAlexaboutno aff

Bibliographic record

VenueÉrès eBooks · 2019
Typebook
Languagefr
FieldHealth Professions
TopicAging, Elder Care, and Social Issues
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtPhilosophy

Abstract

fetched live from OpenAlex

Face a l’allongement de la longevite et a l’entree massive ces prochaines annees des baby-boomers dans le grand âge, il est important d’ameliorer les savoirs sur les dynamiques de vieillissement. C’est l’ambition de cet ouvrage, porte par des travaux internationaux reunissant sociologues et professionnels de soins. Il developpe et enrichit la reflexion autour des experiences du vieillir a partir du concept de deprise. La deprise designe un travail d’amenagement du parcours de vie qui s’appuie sur une serie de tentatives de substitution d’activites ou de relations. Elle suppose une tension entre le sentiment des limites, corporelles et cognitives, et la volonte d’assurer une continuite identitaire mais aussi un desir de s’assurer une presence differente au monde. A contrecourant d’approches reductionnistes, âgistes et sexistes, qui ont construit une image negative du vieillissement, les auteurs, canadiens, francais, allemands, suisses, rendent compte de ces « arts de faire » qui questionnent l’inscription des aines dans le temps et l’espace, le rapport a soi et aux autres mais aussi les disparites sociales et genrees. Ce tour d’horizon montre bien la necessite de considerer les specificites socioculturelles et politiques dans l’analyse des differentes figures du vieillir. Ouvrage publie avec le soutien de la Fondation MUTAC, sous l'egide de la Fondation de l'Avenir.

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)0.005
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: Other
Teacher disagreement score0.014
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0080.018
Scholarly communication0.0060.006
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0130.001

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 head0.042
GPT teacher head0.360
Teacher spread0.318 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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