Participatory/collaborative Urban Planning and Design: Some Theoretical and Methodological Challenges
Bibliographic record
Abstract
This communication argues that participatory/collaborative urban planning and design can be labelled as transdisciplinary research. It discusses some of the theoretical and methodological challenges in order for this area of Environment-Behavior Studies to develop. Indeed, as frequently experienced, this type of applied research is generally left with little or no time and money for theoretical and methodological retroaction. The discussion is structured in three arguments. The first one concerns theoretical development with an examination of the type and value of knowledge produced during participatory processes. The second argument demonstrates the need for some methodological development in terms of innovative strategies and tools. The final argument insists on the need for applying post-facto evaluative procedures to these participatory/collaborative urban planning and design processes. Two case studies of such processes conducted in Quebec City, Canada, are used to illustrate these points. The first one concerns a one year-anda- half process aiming at producing a Planning Development Scheme for Quebec City’s postwar suburbs; the second, describes the process of producing a Master Plan for a sustainable neighborhood on Quebec City's university campus. [SOURCES: 1) DESPRÉS C, FORTIN A, JOERIN F, VACHON G, MORETTI GP, GATTI E (2008) Retrofitting postwar suburbs: A collaborative planning process. In G Hirsch Hadorn, H Hoffmann-Riem, S Biber-Klemm, W Grossenbacher-Mansuy, D Joye, C Pohl, Christian U Wiesmann & E Zemp (eds) Handbook of Transdisciplinary Research. Heidelberg: Springer. 2) DESPRÉS C, BRAIS N, AVELLAN S (2004) Collaborative planning for retrofitting suburbs: Transdisciplinarity and intersubjectivity in action. In RJ Lawrence & C Després (eds) Transdisciplinarity in theory and practice, Futures, 36 (4) : 471- 486. Special issue.; 3) FORTIN A, DESPRES C, VACHON G (2005) Design urbain en collaboration. Bilan et enjeux. In S Lardon (dir) Le diagnostic des territoires, Géocarrefour. Revue de géographie de Lyon, 80 (2) : 145-154. Special issue.; 4) VACHON G, DESPRÉS C, NEMBRINI A, JOERIN F, FORTIN A, MORETTI GP (2007) Collaborative planning and design for a sustainable neighborhood on Quebec City's university campus. In K Thwaites, S Porta, O Romice & M Greaves (eds) Urban Sustainability through Environmental Design, (129-135). London : Routledge.]
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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 | 0.278 | 0.113 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.023 | 0.108 |
| Scholarly communication | 0.036 | 0.023 |
| Open science | 0.009 | 0.022 |
| Research integrity | 0.013 | 0.014 |
| Insufficient payload (model declined to judge) | 0.004 | 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".