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Record W2068871641 · doi:10.1177/1363459308090055

Disruption foreclosed: older women's cancer narratives

2008· article· en· W2068871641 on OpenAlexaff
Chris Sinding, Jennifer Wiernikowski

Bibliographic record

VenueHealth An Interdisciplinary Journal for the Social Study of Health Illness and Medicine · 2008
Typearticle
Languageen
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsMcMaster University
Fundersnot available
KeywordsConceptualizationNarrativeContext (archaeology)PsychologyCurrencyQualitative researchSociology of health and illnessDevelopmental psychologySociologyHealth carePolitical scienceHistorySocial science

Abstract

fetched live from OpenAlex

A challenge has emerged to Bury's (1982) conceptualization of chronic illness as biographical disruption. The idea that certain life circumstances--notably older age or the presence of significant health and social problems--render the experience of chronic illness biographically 'continuous' or 'reinforcing' has gained currency in the social study of chronic illness. This article draws from a qualitative study with women diagnosed with cancer in their 70s or 80s. Respondents' narratives suggest that a long life, especially a life characterized by struggle, does provide a context for the assessment of cancer as non-disruptive. However, the study offers evidence that a long life characterized by sufficiency may also be associated with an assessment of cancer as non-disruptive, and that older age and hardship sometimes render chronic illness especially problematic.Centrally, the article examines respondents' oft-cited commitment to avoid ;dwelling' on illness, highlighting how broad cultural and moral discourses, patterns of social interaction and structures of power combine to foreclose older women's accounts of disruption.

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)0.006
metaresearch head score (Gemma)0.013
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 score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0120.014
Scholarly communication0.0080.009
Open science0.0010.010
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0020.000

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 head0.133
GPT teacher head0.555
Teacher spread0.422 · 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

Citations76
Published2008
Admission routes1
Has abstractyes

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Same venueHealth An Interdisciplinary Journal for the Social Study of Health Illness and MedicineSame topicObesity and Health PracticesFrench-language works237,207