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Record W2953037367

Placemaking through community and adaptable design (The Case of Coffee Park) (First Design Iteration).

2019· article· en· W2953037367 on OpenAlexaboutno aff
Pauline Alamay, Ben Azoulay, Antoine Bacle Taillefer, Katerina Bakogiannis, Imani Nefertari Bernard Guerra, Tyler Boyle, Alejo Davies-Jordan, Jessica Doan, Silvano De la Llata, Erik Enhorning, Philippe Grant, Elijah Herron, Layla Imperatori, Alexander Karczewski, Watts Lily, Kening Liu, Pauline Libongco, Tate LeJeune, Michelle MacEachen, Scott McCallum, Daanya Mirza, Carlo Primerano, Stacy Reyes, Mirya Reid, Lucas Sáenz, Trynity Turnbull, Annick Taylor, Jonathan Task, Elliot White, Cedric Yargeau

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2019
Typearticle
Languageen
FieldEngineering
TopicArchitecture and Computational Design
Canadian institutionsnot available
Fundersnot available
KeywordsCommunity designPlacemakingBrainstormingParticipatory planningUrban planningContext (archaeology)Urban designPublic spaceSociologyEnvironmental planningEngineeringArchitectural engineeringBusinessCivil engineeringGeographyPolitical scienceMarketing
DOInot available

Abstract

fetched live from OpenAlex

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. 
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\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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.260
Threshold uncertainty score0.707

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.044
GPT teacher head0.248
Teacher spread0.205 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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