UD Co-Spaces
Bibliographic record
Abstract
UD Co-Spaces (Urban Design Collaborative Spaces) is an integrated, tabletop-centered multi-display environment for engaging the public in the complex process of collaborative urban design. We describe the iterative user-centered process that we followed over six years through a close interdisciplinary collaboration involving experts in urban design and neighbourhood planning. Versions of UD Co-Spaces were deployed in five real-world charrettes (planning workshops) with 83 participants, a heuristic evaluation with three domain experts, and a qualitative laboratory study with 37 participants. We reflect on our design decisions and how multi-display environments can engage a broad range of stakeholders in decision making and foster collaboration and co-creation within urban design. We examine the parallel use of different displays, each with tailored interactive visualizations, and whether this affects what people can learn about the consequences of their choices for sustainable neighborhoods. We assess UD Co-Spaces using seven principles for collaborative urban design tools that we identified based on literature in urban design, CSCW, and public engagement.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.049 | 0.010 |
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".