Dwelling on Loneliness: Structural Drivers of Social Resiliency, Belonging, and Well Being
Bibliographic record
Abstract
Using the lens of common residential typologies found in Canada, this paper examines the possibilities structural drivers (the built environment) might offer to promote social interaction and help address the emerging state of chronic loneliness being experienced in the country. Specifically, the question is how might architects begin to dismantle common spatial constructs grounded in autonomy in search of typologies founded on negotiable space that supports the act of coming together and exchange? Research exists regarding attitudinal, relational, and cultural drivers of connection, but the impact of early, architecturally driven conceptual design decisions and their effect on social interaction and sociability remains limited. Where knowledge does exist, the trend is towards using a qualitative metric such as case study, precedent, or anecdotally based post occupancy evaluation. Through the use of simulation software known as FLUID Sociability, comparative measurements can be made between design proposals to reveal the potential effectiveness of structural drivers in promoting human connectedness and social interaction earlier in the design process. To advance the ideas, a hybridized seminar-design based graduate level course was developed to create testable hypotheses and emergent design proposals involving four common residential typologies. The typologies were subsequently tested for social performance using the aforementioned software. The results present a comparative working methodology whereby designers and architects can evaluate design options from the perspective of social interaction, and thereby provide enhanced design rationales to pro actively build more socially resilient dwellings and communities.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".