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Record W2331147482 · doi:10.1177/1471301210392979

Exploring positioning in Alzheimer Disease through analyses of family talk

2011· article· en· W2331147482 on OpenAlexaff
Barbara Purves

Bibliographic record

VenueDementia · 2011
Typearticle
Languageen
FieldArts and Humanities
TopicLanguage, Discourse, Communication Strategies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDementiaConversationInterviewNegotiationPsychologyConversation analysisDiseaseFamily memberEveryday lifeDevelopmental psychologyMedicineCommunicationSociologyFamily medicine

Abstract

fetched live from OpenAlex

The ways in which people with dementia are positioned through talk has received considerable attention, but to date there has been little exploration of such positioning in everyday family life. Given the importance of family in caring for persons with dementia, it is critical that we understand, first, how family members position themselves and each other as they negotiate changes associated with dementia and, second, the implications of that process, both for individual members and for the family as a unit. In this study, two complementary approaches were used to explore positioning in the family of a woman with dementia. The first used interviewing to reveal how family members positioned themselves and each other in their conscious reflections about dementia. The second, drawing on conversation analysis, highlighted how they positioned themselves and each other in their everyday conversations together. Implications for the study of dementia in the family are discussed.

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)0.005
metaresearch head score (Gemma)0.010
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 score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0080.011
Scholarly communication0.0060.005
Open science0.0010.006
Research integrity0.0010.002
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 head0.528
GPT teacher head0.372
Teacher spread0.156 · 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

Citations19
Published2011
Admission routes1
Has abstractyes

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