Suburban Exaptation: Densification Without Demolition
Bibliographic record
Abstract
Wood framing, widely available and easy to assemble, has come to embody the ideal of a modular architectural system but not the image. Despite this inherent ability to enable change, its rigid implementation through the single family type has created an urban monoculture which encompasses two thirds of the Canadian population. As zoning rules are loosened to promote the creation of “missing middle” density housing, the greatest barrier to accommodating this need has become the suburban house itself. Whether through lot splitting, infills, or property aggregation, these single family communities can be densified, but only at the expense of premature demolition. Their replacements, constructed using the same techniques as the homes they replace, call into question the misappropriation of wood framing’s flexibility. By viewing these existing homes not as barriers to densification but as the means for its rapid implementation, this thesis approaches wood framing as a modular system in place of its current use as a disposable commodity, embedding the opportunity for density within the single family house. Leveraging the similarities between low and high density housing types in Calgary, one of Canada’s most suburban and fastest growing cities, the proposal seeks to enable the densification of the Calgarian suburbs without demolition, subverting existing zoning and visual approaches in individually subtle but exponentially impactful ways.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".