Dynamics of Daily Ageism and Attitudes for Healthy Aging: Cross-Cultural Analysis of the Subjective AGES Project
Bibliographic record
Abstract
Abstract The proposed symposium provides a global perspective regarding antecedents, correlates, and consequences of views on aging based on the Subjective AGES (Aging within Global everyday Ecological Studies) consortium. This culture-informed approach highlights the contextual and dynamic influences of daily ageism, attitudes, and behaviors across different temporal perspectives. We enrich the existing body of knowledge by including a broad variety of cultures and investigating how daily ageism and attitudes connect to daily indicators of health and well-being. First, Neupert et al. characterize the amount of day-to-day fluctuation in daily ageist attitudes across daily diary studies from 10 countries and show cross-cultural differences in the impact of those fluctuations on daily memory functioning. Wirth et al. use daily diary data from Germany, Israel, Türkiye, and USA and find that people with more age-related losses endorse more ageist attitudes than those with fewer losses. Lee et al. examine three exposure contexts as potential sources of daily ageist attitudes in Canada, finding that greater overall social media use, but not TV viewing or neighborhood age composition, was significantly associated with greater experiences of ageism in daily life. Röcke et al. connect fluctuations in subjective age with mobility in Switzerland, showing that participants who report higher flexibility concerning environmental and personal challenges travel further away from home on days when feeling younger than their actual age. Our findings shed light on country-specific and global relationships between views on aging and development. We showcase how experiences of aging are shaped by contextual and dynamic influences.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".