Inhabitable Bridge Infrastructure: A Reappropriation of the Street from Vehicular to Pedestrian Scale
Bibliographic record
Abstract
For the past century urban infrastructures have been designed primarily with automobile use in mind. The built environment consequently reflects a neglect of the human scale, that is, pedestrians. This thesis looks at existing contemporary bridges and explores ways of bringing pedestrian-scaled activity and vitality back onto the bridge, thereby breaking the confines of vehicular bridges to create a continuum of the urban environment on both ends. This thesis investigates methods of integration and coordination of vehicular and pedestrian traffic as a way to maintain the bridge as a “connector” for transport purposes, resulting in a future where bridges may facilitate a higher quality urban environment. The site for this thesis is the Jacques Cartier Bridge, a vehicular bridge that spans the St. Lawrence River in Montreal. This thesis examines the history of the street versus the road, place versus non-place, mobility versus transport and the influence of the Megastructuralist movement in Montreal as applicable elements for future bridge design. This thesis will also find ways to reacquaint itself with the estranged concept of the inhabitable bridge and demonstrating how it can be reintegrated into current and future infrastructural bridge concepts.
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 | 0.001 | 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 | 0.001 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".