At, with and beyond risk: expectations of living with the possibility of future dementia
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.042 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.037 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".