Integrational Structuring: A Holarchic Strategy for Housing the Aging Population
Bibliographic record
Abstract
Canadian society is facing a marked demographic shift as the baby boom generation ages. By 2031 almost 25 percent of Canadians will be over sixty-five; many of those will be north of eighty and the oldest boomers will be turning eighty-five. One person in four will be a senior. \n \nThe lack of acceptable intermediate solutions between independence and institutionalization has been pointed out as one of the significant problems facing elderly persons; traditional ‘institutional’ care which keeps older people apart and medicalizes old age, is no longer desirable. Likewise, the ‘golden ghettoes’ model may be appealing to those who can afford it but does not contribute to producing diverse, inclusive urban places. This thesis is an exploration of an alternative strategy. It investigates how architecture can provide a platform for social connection in a residential environment that allows in equal measure both independence without isolation, and informal community with safety and security. The design proposal establishes five architectural strategies which address the fundamental spatial implications of encouraging aging-in-place. This exploration is supplemented with a cohousing strategy, providing a formal organizational tactic that encourages groups of residents to mutually support each other, strengthening social inclusion and reducing the use of formal care and support only where absolutely necessary. \n \nThe methodology employed examines the mutually dependent and interactive scales of City, Neighbourhood, Building, and Dwelling in conceiving of housing for an aging population that becomes a catalyst of urban integration and community regeneration.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.017 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".