Bibliographic record
Abstract
With increases in life expectancy, many people can expect to spend one quarter or even one third of their life in old age. Yet, although preparation for retirement has become increasingly common, preparation for old age, in areas such as housing and care, leisure activities, social relationships, finance, and death and dying, is less well understood. In this symposium, four panelists, two from Germany and two from Hong Kong, will present and discuss cross-cultural findings on preparations for old age. Although the focus is on Germany and Hong Kong, data on US and Japan will also be discussed to draw conclusions on East versus West distinctions. First, Rothermund and colleagues will discuss cultural differences in attitudes toward old age. They asked to what extent old age was perceived to be a period of rest/relaxation versus active engagement, and by whom. Then, Lang and colleagues will present cross-cultural findings on the timetables for starting and completing preparations for late life. Next, Fung and colleagues will discuss how religious belief and acceptance of death might account for cross-cultural differences in preparation for death and dying. Last but not least, Cheng will discuss how several global trends, such as financial uncertainty/pressure, new housing structures and living arrangements, and the popularity of social media, have changed the meaning of aging and preparation for old age. Finally, Dave Ekerdt will discuss the implications of these findings for the emerging field on late-life preparations, and for examining aging phenomena across diverse cultures.
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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".