Strategies for More Inclusive Municipal Participatory Governance and Implimenting UN-Habitat's New Urban Agenda: Improving Consultation and Participation in Urban Planning Decision-Making Processes through Rapid Ethnographic Assessment Procedures
Bibliographic record
Abstract
Based on the findings of an urban legal anthropology project in Toronto, Canada that tracked municipal decision-making practices in relation to development, redevelopment, and heritage preservation in the city and the often unforeseen and unacknowledged effects these can have on marginal, transgressive, and subaltern (subcultural) communities and their community cultural spaces and practices, this article will first turn to a few neighbourhood examples of public consultation processes underway in Toronto and observations of visual (vocal) resistance to faulty consultation practices. These examples reveal some of the realities of public consultation design in Toronto and how it is experienced on the ground where not all segments of a neighbourhood, community, or those who use a space targeted for (re)development are effectively included or accessed. This article will also examine an example of urban artistic protest to current consultation and development practices before turning to existing sustainable (re)development frameworks, theory, and best practices. Finally, the paper will engage with Sherry Arnstein’s ladder of citizen participation to move towards an argument for the application of Rapid Ethnographic Assessment Procedures to municipal public and community consultation practices as a means of effective citizen engagement in municipal (re)development and local cultural heritage preservation decision-making processes that are in line with the principles of the New Urban Agenda.
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 | 0.079 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.020 | 0.030 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".