Legislating Tolerance: Article 976 of the Civil Code of Quebec and its Application to Mixed-Income and Mixed-Use City Redevelopment Projects
Bibliographic record
Abstract
I first examine the increasing need for tolerance required for the cultural sustainability of city redevelopment projects that seek to establish communities of a mixed-use or mixed-income variety. Next, some difficulties that arise in terms of inequality, clashing differences, and a lack of inclusion felt by those within these redeveloped spaces in the urban cores of our cities are discussed with reference to Boaventura de Sousa Santos’s notion of cosmopolitan legal struggles and the subaltern cosmopolitan contact zones generated within the small social spaces of mixed-use and mixed-income developments in the urban core. I then undertake a discussion of article 976 of the CCQ, where a form of legislated tolerance can be observed, before I examine the differences in the treatment of neighborhood nuisance under article 976 in comparison to its treatment elsewhere. Finally, the discussion culminates by drawing the lessons learned from article 976 back into the discussion of Santos’s cosmopolitan legality, the drumbeat of city redevelopment projects in the urban cores of our cities, and the potential of harnessing hegemonic legal tools in a non-hegemonic or counter-hegemonic manner, in order to work towards more tolerant and culturally sustainable cities.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.016 | 0.024 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.008 | 0.007 |
| 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".