MétaCan
Menu
Back to cohort
Record W2803004736 · doi:10.1111/1467-9566.12731

At, with and beyond risk: expectations of living with the possibility of future dementia

2018· article· en· W2803004736 on OpenAlexfundno aff
Richard Milne, Ana Diaz, Shirlene Badger, Eline M. Bunnik, Karine Fauria, Katie Wells

Bibliographic record

VenueSociology of Health & Illness · 2018
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
FundersSeventh Framework ProgrammeAlzheimer Society“la Caixa” FoundationNational Academies of Sciences, Engineering, and MedicineAlabama Farmers Federation
KeywordsDementiaDiseaseVigilance (psychology)PsychologyCognitionTest (biology)PsychiatryMedicineCognitive psychologyPathology

Abstract

fetched live from OpenAlex

Biomedical research aimed at the development of therapies for chronic and late-onset conditions increasingly concentrates on the early treatment of symptom-less disease. This broad trend is evidenced in prominent shifts in contemporary dementia research. Revised diagnostic criteria and new approaches to clinical trials propose a focus on earlier stages of disease and prompt concerns about the implications of communicating test results associated with the risk of developing dementia when no effective treatments are available. This article examines expectations of the implications of learning test results related to dementia risk, based on focus group research conducted in the UK and Spain. It points to the extended social and temporal aspects of the dementia risk experience. Three key dimensions of this risk experience are elaborated: living 'at risk', represented in efforts to reduce risk and plan for the future; 'with risk', through vigilance towards cognitive health and earlier or prolonged contact with healthcare services; and finally, 'beyond risk' through a cessation of the self in its current social, legal and financial form. A virtual abstract of this paper can be viewed at: https://www.youtube.com/channel/UC_979cmCmR9rLrKuD7z0ycA.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.011
GPT teacher head0.323
Teacher spread0.312 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations49
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueSociology of Health & IllnessSame topicDementia and Cognitive Impairment ResearchFrench-language works237,207