“This is wrong and we will support you”: The (restricted) role of resident-led neighbourhood-level planning teams in residential displacement
Bibliographic record
Abstract
Using qualitative data collected from 2013-2017, this paper investigates how resident-led planning teams working within Hamilton, Ontario’s Neighbourhood Action Strategy (NAS) responded to gentrification and displacement. Highlighting case studies of three neighbourhoods, our findings reveal that resident groups can act as both sites of support for gentrification and sites of resistance to residential displacement. Our findings complicate the common narrative that posits residents as powerless in the face of gentrification, showing how residents resisted coercive displacementefforts. The case studies expose concrete strategies used by residents: engaging directly with City Hall and developers, countering exclusionary neighbourhood attitudes through community dialogue, and supporting tenant organizing. However, findings also highlight how differences among residents (particularly class, race, and length and type of tenure) shaped both the nature and effectiveness of resistance in this municipally-supported initiative, and identify the need for more attention to preventing displacement within formal planning processes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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 teacher head, 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".