Functional and Aesthetic Factors for Well-Being in Age-Friendly Residential Areas (AFRA) in Poland: An International Comparative Perspective
Bibliographic record
Abstract
(1) Background: A precise and comprehensive diagnosis of the needs of older adults is the basis for developing concepts of aesthetic functional and spatial arrangements of public open spaces in residential areas that meet their expectations, termed “age-friendly residential areas” (AFRAs). The primary objective of the research was to determine the needs of older people concerning their preferences for the development of AFRAs. (2) Methods: This research was conducted on the basis of a survey conducted from October 2021 to April 2022, involving 1815 older citizens from Poland, Germany, the United Kingdom, the United States, Canada, Croatia, Italy, Lithuania, and Slovakia. The research aimed to determine the needs of older people regarding their preferences for the development of AFRA public open spaces. The developed research approach made it possible to answer the following research questions: (1) What are the needs of different generations of older adults, differentiated by gender and lifestyle, in terms of spatio-functional and landscape aspects with regard to the open spaces of residential estates? (2) Do older citizens from different countries living in various estates (single-family, multi-family) have the same expectations towards AFRAs? (3) Results: The research results showed a high convergence of preferences among older people regardless of gender, age group, or type of residential estate they live in (multi-family/single-family). Slight differences in AFRA preferences were noticed between Polish and non-Polish older adults, most often due to cultural habits. A correlation between the landscape attractiveness and aesthetics of the estate and the comfort of life for the older population, as well as their impact on the final assessment of the estate, was confirmed. As a result of the research, 33 spatio-functional and 16 landscape factors of AFRAs were identified and ranked.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".