A New Agenda for Local Democracy: Building Just, Inclusive, and Participatory Cities
Bibliographic record
Abstract
There is a crisis of growing inequality in Canadian cities. As COVID-19 spread through Canadian cities beginning in spring 2020, racial inequities became apparent, including biased enforcement of bylaws and higher coronavirus rates amongst racialized and vulnerable communities. These health care injustices exposed municipal decisions that have led to negative outcomes for marginalized groups, especially in policing, community safety, housing, homelessness, and bylaw enforcement. In response, cities have been called upon – again – to change their governance models to allow for greater participation and better include the voices and lived realities of racialized and marginalized people in decision-making processes. In a post-pandemic period of city building, where socio-economic and racial inequalities have been exposed, municipalities must incorporate social equity and explicit race-based lenses in their decision-making and reimagine their governance practices. This paper sets out the ways in which municipal governance frameworks have worked to exacerbate inequality, with suggestions on how cities can design more democratic and responsible models. These include greater engagement with equity-deserving communities and community bodies, modifications to existing governance models, and legislative changes.
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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 | 0.027 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.024 | 0.049 |
| Scholarly communication | 0.022 | 0.017 |
| Open science | 0.003 | 0.025 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.011 | 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".