<scp>BEYOND THE TRIAGING OF NEGLECTED THINGS</scp>: Connecting Place and Participation Across an Urban System
Bibliographic record
Abstract
Abstract What is the relationship between top‐down governance reform and place‐based participatory and deliberative spaces? In this article I argue that in Toronto, an urban system of public participation and deliberation is intimately interwoven into partisan scalar restructuring processes, as well as enduring tensions over the ways and means by which the public can have authoritative input on solving local issues. Regardless of top‐down political manoeuvring, the public mobilizes in various spaces across the city, but the urban system remains disconnected and geared towards triaging. This means that the public must work autonomously across the city and within the crevices of city processes, prioritizing how to make gains on issues that they feel are important. I discuss how to move beyond this by building on deliberative systems theory and findings from interviews with local city staff and residents, and through an analysis of public deputations at the official Special Committee on Governance. Ultimately, there is a need for spatially integrated opportunities for more people to come together and assemble in different ways. Some of these will align with autonomous activities, some are liminal and woven within institutional partners, and others are more about geographical bridge building.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.016 | 0.065 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".