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Record W2164296212 · doi:10.1177/0011392107073303

Older Women and ‘Frailty’

2007· article· en· W2164296212 on OpenAlexaffabout
Amanda Grenier, Jill Hanley

Bibliographic record

VenueCurrent Sociology · 2007
Typearticle
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsResistance (ecology)NarrativeSociologyGender studiesOlder peopleGerontologyFocus groupSocial psychologyPsychologyMedicineAnthropology

Abstract

fetched live from OpenAlex

The concept of ‘frailty’, as used within public health and social services, represents a powerful practice where cultural constructions, the global economic rationale of cost restriction and the biomedical focus on ageing collide as inscriptions on the bodies of older women. This article draws on complex forms of resistance witnessed within three separate studies: narrative interviews on ‘frailty’, semi-structured interviews and participant observation in community organizations with older women in Montreal and Boston. Findings reveal how older women exercise resistance in complex ways, both consciously subverting and coopting the notion of ‘frailty’ on an individual and collective level. Such resistance demonstrates the tensions between undermining dominant notions of ageing, and fulfilling prescribed gendered and age-based assumptions about older women and their bodies. The intersections and forms of older women’s resistance challenge social constructs, social expectations and what is recognized as resistance.

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)0.003
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.023
Scholarly communication0.0030.003
Open science0.0000.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.097
GPT teacher head0.466
Teacher spread0.368 · 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

Citations83
Published2007
Admission routes2
Has abstractyes

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