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Record W287421698 · doi:10.1353/cja.2007.0017

S. Katz. Cultural Aging: Life Course, Lifestyle and Senior Worlds. Peterborough, ON: Broadview Press, 2005.

2006· article· fr· W287421698 on OpenAlexaff
Amanda Grenier

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2006
Typearticle
Languagefr
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsMcGill University
Fundersnot available
KeywordsSoulHumanitiesSociologyArtGerontologyPhilosophyMedicineTheology

Abstract

fetched live from OpenAlex

RÉSUMÉ Cultural Aging: Life Course, Lifestyle and Senior Worlds présente onze essais regroupant dix ans de réflexion de Katz (1994–2004) sur les “problèmes” du vieillissement culturel. Le livre comprend deux parties. La première, Aging, Life Course and the Cultural Politics of Expertise, porte sur les pratiques historiques, textuelles, politiques et culturelles du savoir, de l'expertise et de la vérité. La deuxième, Lifestyle and the Fashioning of Senior Worlds, pose la problématique des modèles de vieillissement associés à la culture. Katz réfère à des théories contemporaines pour repenser les questions liées à l'étude du vieillissement et soulève des questions essentielles sur les formes de vieillissement et les attentes des personnes âgées dans la société occidentale. Cultural Aging est un exemple d'une gérontologie critique qui repousse les limites de la discipline établie et soulève des questions découlant d'études interdisciplinaires et de connaissances locales.

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.079
Threshold uncertainty score0.266

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.013
Science and technology studies0.0020.002
Scholarly communication0.0030.008
Open science0.0020.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0790.030

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 head0.018
GPT teacher head0.242
Teacher spread0.224 · 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
GenreReview

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
Published2006
Admission routes1
Has abstractyes

Explore more

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