Placemaking through community and adaptable design (The Case of Coffee Park) (First Design Iteration).
Bibliographic record
Abstract
Using participatory planning and community design methodologies (i.e. open planning, pattern language design, placemaking, community planning charrettes, planning-in-situ and wikiplanning) this project explores solutions to revitalize Coffee Park -- a small park along the CN railway in West Montreal. This is a complex site that shows issues of unsafety, lack of mobility and sense of place. The objective of this project is to integrate the park to its larger urban context to improve the mobility, safety and overall quality of life in this public space. After a series of visioning workshops, brainstorming sessions, two community planning charrettes and an open planning exercise, this project incorporates inputs from stakeholders, students and ordinary citizens into a collaborative urban design project. The project proposes strategies of urban re-stitching and regeneration through adaptable design and open community planning. \n \nWith the objective of encouraging future adaptations and transformations, this project is published under a Creative Commons license. Adopt and adapt these ideas (but cite and acknowledge accordingly).
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 | 0.010 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.015 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".