Exploration of a culturally appropriate design for a Retirement Community for Muslims of South Asian origin
Bibliographic record
Abstract
This research is an exploration of suitable environmental design elements for a retirement community for seniors of South Asian origin. Most geriatric, social and health sciences literature discusses the services needed and the problems of loneliness and social isolation faced by older adult immigrants. Currently, the existing models of living arrangements available for seniors in Canada are very generic and lack cultural accommodation. This research was the result of personal experiences with my parents’ situation as they arrived in Canada in the post-retirement stage of life. My family searched for suitable residential options and found a lack of them and scarcity of appropriate solutions for Muslim seniors of South Asian origin. Through my literature review I found four major problems faced by South Asian seniors which were: Loneliness and isolation, loss of independence and autonomy, lack of transportation, and lack of options to maintain health and wellness especially in the winter. The South Asian community is a very large and diverse community, although there are many features common between them all, I had to narrow down the scope of my research to discuss the problems faced by Muslim seniors of the community due to the restrictions of time and resources. I used three methods: a case study, discussion with a focus group, and interviews/meetings with other consultants/experts/stakeholders and family members. I found that as architectural design has become globalized in the past few decades, there are certain nuances that make spaces culturally suitable for the seniors. Seniors of ethnic populations are the most powerless, least influential, and the most forgotten segment. There is a lack of environmental design research on the needs of South Asian seniors in North America and this paper lays the groundwork to build on future research.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".