Infrastructural architecture: social design for the public realm in underground transit systems
Bibliographic record
Abstract
There’s a certain allure and poeticism to mass transit, from buses, to streetcars, and trains. It’s curious that a strictly infrastructural marvel of engineering houses such an honest and diverse application of shared architecture, mutual in it’s urban scope. In many ways, the architecture of these utilitarian transit spaces (subways most notably), are comparable in their role to that of the public square, court, or forum. There is an untold architectural relationship within these urban environments between subways as a space of movement, and as a place of activity. This thesis aims to re-examine subways under this lens. To posit that subways offer more to the urban fabric than a functional vessel for movement, and are indeed vital at providing opportunity for social life to flourish in an urban context. Questions of democratizing space, spatial legitimacy, functionalism, and the dichotomy between space and place, arise when examining these constructs of subterranean infrastructure. These relationships will be explored by studying and reimagining a particular site along the City of Toronto’s subway system, specifically; Spadina Station. It is the intersection of both the University-Yonge Line, the Bloor Line, as well as the terminal to the Spadina Avenue streetcar. The key methods of research for this study include studying, drawing, and photographing the space to better understand it’s prescriptive needs, and to inform a modified architectural response and proposal. Ultimately, this project aims to be didactic in its thinking with regards to infrastructural architecture through proposal work. The core of transit is the people who use it, and it must be understood that these people interact socially with their surroundings, far beyond just the isolated motions of coming and going. We must ask how utilitarian infrastructure can shift it’s functional role in cities to reclaim the public realm as a space of communal activity, and shared program.
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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 | 0.002 |
| 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 | 0.025 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 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".