Sustainability for whom? Cities and buildings through the lens of older people
Bibliographic record
Abstract
Abstract As we move towards larger and more complex urban developments and with increasing occurrences of extreme weather resulting in significant environmental, societal and economic impacts, it is no longer a question that cities around the world must aim for sustainability. The past few decades have seen efforts by many countries to tackle these critical issues. At the same time, many countries also face significant demographic changes, with almost a quarter of their population over 65 years will be ageing in place, in their own homes. Yet cities, particularly our inner-city built environments, are spaces that are usually imagined, planned and structured for a younger, working-age demographic. This paper discusses the current gap in knowledge in addressing sustainability of our cities and buildings, and proposes a new way of engaging people who are often forgotten, yet they have many years of experience and wisdom about how to live sustainably: the older people. Two examples of ongoing research with older ‘citizen scientists’ are presented. Both cases demonstrate that it is critical to consider cities and buildings from the eyes of older people in society.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.027 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.005 |
| 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".