Gorilla Park: A Sustainable Space for All (Mobility pilot project)
Bibliographic record
Abstract
This project explores urban design and urban systems solutions to address issues of shared mobility, accessibility and urban fragmentation. It is a pilot project to create a park and a shared mobility hub in the borough of Rosemont-La-Petite-Patrie in Montreal. This is to be a node of many in a metropolitan-wide shared mobility system. A shared mobility approach to city planning incorporates notions of Transportation Oriented Development (TOD) and Pedestrian Oriented Development (POD) and links it to notions of smart cities and autonomous transportation. The challenge at hand was to create a public space that incorporates these questions as well as notions of placemaking, community planning and open urbanisms. \nThe project is part of an urban design studio taught in the Department of Geography Planning and Environment at Concordia University in Montreal, and it takes place in the context of the first edition of the CitéStudio Montreal program, which fosters collaborations between academics, students and the city government. \nThe solutions explored in this project were conceived by the students of URBS333 - Urban Laboratory (class of 2019-2020) under the supervision of the instructor (S. De la Llata) and in collaboration with stakeholders and neighbours of Gorilla Park. The solutions are divided into five thematic axes (Sustainability, Mobility and Accessibility, Community Engagement, Hard Design and Soft Design).
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 | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 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".