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Record W4214620994 · doi:10.4000/books.pur.151465

Vieillir en société

2019· book· fr· W4214620994 on OpenAlexaboutno aff

Bibliographic record

VenuePresses universitaires de Rennes eBooks · 2019
Typebook
Languagefr
FieldHealth Professions
TopicAging, Elder Care, and Social Issues
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Comment rendre compte de la pluralité des expériences du vieillir, de leur transformation et des manières dont nos sociétés en régulent les tensions, sinon en les replaçant dans leurs contextes et leurs dynamiques sociales ? Dans le prolongement des analyses de Simone Pennec à l’université de Bretagne Occidentale (Brest) et à partir d’objets et de terrains d’études variés en France principalement, et aussi en Belgique, au Brésil, au Canada, en Suisse, au Mexique, cet ouvrage analyse les manières dont les individus articulent leurs différents engagements au cours de la vie. Il montre comment certaines manières d’avancer en âge peuvent être soutenues ou au contraire déqualifiées. Les quatre parties de l’ouvrage rendent compte des effets des catégorisations des politiques publiques, de la participation des personnes vieillissantes aux différents espaces sociaux, du statut et des expériences des personnes et de leur entourage face aux transformations liées au vieillissement et du travail de soin, de la diversité de ses contextes, de ses registres et de ses acteurs. Cet ouvrage est destiné à des enseignants, des étudiants et des chercheurs en sciences sociales, à des praticiens de l’intervention sociale et des professionnels de santé, comme à l’ensemble des acteurs professionnels, politiques, militants ou citoyens concernés. Il a été coordonné par cinq enseignant·e·s-chercheur·e·s en sociologie : Françoise Le Borgne-Uguen (UBO-Brest), Florence Douguet (UBS-Lorient), Guillaume Fernandez (UBO-Brest), Nicole Roux (UBO-Brest) et Geneviève Cresson (Université Lille 1).

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)0.003
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 score0.028
Threshold uncertainty score0.093

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0060.007
Scholarly communication0.0090.005
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0280.004

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 head0.025
GPT teacher head0.312
Teacher spread0.288 · 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".

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Citations2
Published2019
Admission routes1
Has abstractyes

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