‘The calendar is just about up’: older adults with multiple chronic conditions reflect on death and dying
Bibliographic record
Abstract
Drawing on data from in-depth interviews with 35 men and women aged 73-91, this article examines the ways in which older adults with multiple chronic conditions talk about and prepare for death and dying. While the focus of the original study did not include questions concerning the end-of-life, the majority of our participants made unprompted remarks regarding their own and others' mortality. The participants discussed the prevalence of death in their lives as it related to the passing of significant others, as well as their own eventual demise. Additionally, the men and women expressed hopes and fears about their impending death, in particular with respect to prolonged pain and suffering, institutionalisation, and a loss of mental acuity and independence. Many of our participants also described their end-of-life plans, which included making funeral arrangements, obtaining living wills, and planning their suicides. They further reported a number of barriers to their planning for death, including a lack of willingness on the part of family members to discuss their wishes as well as a scarcity of institutional resources and support. We discuss our findings in relation to the extant research concerning older adults' experiences of death and dying, as well as Glaser and Strauss' (1971) theory of status passage and Marshall's (1986) conceptualisation of authorship and the legitimation of death.
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| 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".