Urban Conflicts and Socio-Territorial Cohesion: Consensus-Building and Compromise in the Saint-Michel Neighborhood in Montreal
Bibliographic record
Abstract
Our research highlights the structuring eff ect of initiatives that mobilize social economy and community action resources with the aim of promoting the conversion of local spaces and the implementation of a dynamic of local development and socioterritorial inclusion.Using the case study of the establishment of La TOHU in the Saint-Michel neighbourhood in Montreal (Quebec, Canada), for which we conducted a literature review and an interview survey, we show how urban confl icts contributed to the construction of a cohesive environment.In the path taken by Saint-Michel, one of the most sensitive neighbourhoods in Canada, our confl ict analysis sheds light on (1) the relationship between urban confl icts and legitimate representation for sites of consensus-building, (2) the importance of the instances allowing for debate and discussion between the various types of actors (social, business community, public) such as to generate strong coalitions centered on the social development of the local community and the improvement of the quality of life for citizens, and (3) the relationship between consensus-building among the actors and the development of compromises for the territory under study.Th e debates provoked by the confl icts thus allowed for the social construction of rallying points, which in turn promoted the reaching of compromises, in this case, the one leading to the establishment of La Consensus Building and Compromise in the Saint-Michel Neighbourhood in Montreal TOHU.However, although La TOHU was a success as a strategy of integration and socio-territorial connectivity, the roots of the borough's socio-economic problems have not been resolved: Saint-Michel is still a poor neighbourhood in which socio-territorial exclusion has not disappeared.Finally, the 2008 riots which took place in Montreal-North, an adjacent neighbourhood, point to an important direction to pursue in our continuing research on the role and place of confl icts in socio-territorial regulation: the analysis of ethnic riots and confl icts related to social integration.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".