Leslieville: A Neighbourhood in Transition, A Community Divided : Understanding the Changing Politics of Space in a Toronto Neighbourhood
Bibliographic record
Abstract
This paper aims to tell the story of Leslieville, a small neighbourhood in Toronto's east end, from its early settlement in the 1850s to the present. Looking back at the area's progression from farming village, to working-class industrial centre, to gentrifying creative hub, provides the historical context for a further consideration of the current challenges and conflicts that are impacting the community today. In 2008 a land dispute over a proposed big-box style retail development divided the community and instigated a yearlong battle at the Ontario Municipal Board between Toronto city council and private developers. In tracing the historical growth of Leslieville and analyzing the current development issues, this study examines how urban development and cultural policy have influenced the transformation of this unique Toronto neighbourhood. An application of the theoretical literature on gentrification and photographs are provided in order to supplement the analysis. By identifying Leslieville as a neighbourhood in transition and examining it as a case study in the process and impact of gentrification and neighbourhood change this research contributes to a further understanding of the nature of urban space and how it should be developed to serve the interests of Toronto's diverse population.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.012 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".