An ‘all-world ageing’ perspective and its wider ethics of care: An empirical illustration
Bibliographic record
Abstract
Recent commentaries have proposed 'all-world ageing' as a new perspective for social scientific ageing research. It is based on the theoretical observation that the ageing process involves all forms of entities co-ageing relationally with each other, and with their surrounds. Its disciplinary implications hence being that what we categorize as ageing in social scientific ageing research should not be limited to human bodies, and that ageing non-humans should be brought under its purview. To empirically illustrate these theoretical and disciplinary assertions, and explore their implications, the current paper reports a study of how people co-age with non-humans they interact with in their daily lives. Sixteen people aged 66-90 were interviewed, ten of them also being observed at those times. The findings show some intricate and diverse relations that involve their co-ageing with varied biological entities and nature surrounds (such as plants, domestic animals and green spaces) and varied non-biological entities and non-nature surrounds (such as materials, technologies, accommodations, organizations and infrastructures). Meanwhile, important crosscutting themes - including lifespan, function and aesthetics - emerge as objectives of care, valued and exercised in broad terms. This empirical reconnaissance shows the potential for an all-world ageing perspective to engage diverse societal challenges and inform diverse areas of practice as part of a wider ethics of care. From it, a number of important considerations and undertakings arise for future scholarship.
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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 | 0.036 | 0.054 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.013 | 0.074 |
| Scholarly communication | 0.008 | 0.017 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".