ZERO HOUS[ING] 1:1 Prototype + Process: Collaborative and Experiential Education in the Global Housing and Climate Crisis
Bibliographic record
Abstract
Zero Hous[ing] is a recently built energy-neutral midrise housing prototype that investigated alternative sites, and alternative forms of practice and production. It used prefabrication and a carbon-sequestering palette to address the housing affordability and climate crisis. While it was produced and reads as a single-family house— it was designed to work as housing for metropolitan areas. This project considers urban typology, architectural design for aesthetics, function, health and well-being, and innovative construction methodologies to look at this problem from the bottom-up and across sectors. The objective was to build demand with consumers and industry for net-zero energy and carbon-sequestering housing by making a healthy and attractive architecture, creating site location and construction efficiencies, and demonstrating through this built prototype and its life-cycle cost and energy analysis, that it might be accessible to the many rather than the few. We realized this building with custom prefabrication and a deeply integrated design process engaging a cross-disciplinary team of professionals, educators, builders and students in all stages of the work. This project is remarkable for the ambition and scope of its definition of sustainable design (urban design, carbon footprint, energy use and construction methodology) and for its recognition that, in order to change existing paradigms we need to actively interact, and through experiments like this, develop new ways to design, build, and live collaboratively. This educational project integrated architecture, engineering, and business faculty and students at Ryerson University, Toronto Canada and an industry construction/education partner called The Endeavour Centre. We collaborated on this one-to-one scale prototype using Passive House principles, and prefabrication as an ethic. We built it using our industry partner’s team of apprentice carpenters and it is now being enjoyed as a full-time residence for its owner while we monitor its performance.
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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".