Rethinking Moral Work in the Context of Gentrification
Bibliographic record
Abstract
Gentrification is increasingly framed as a moral issue, where competing actors struggle to define legitimacy, justice, and belonging. This article examines how these moral narratives shape public discourse in Hochelaga-Maisonneuve, a gentrifying neighborhood in Montreal. Through a qualitative analysis of media coverage, promotional materials, and public statements, and using the Economies of Worth framework developed by Boltanski and Thévenot, we examine the types of moral justifications employed by developers and community organizations in this neighborhood. Our study shows that both sides invoke common ideals such as sustainability, community, and quality of life, yet do so in divergent ways, producing moments of moral overlap as well as deeper normative conflicts. We argue that gentrification is not only a spatial and economic process but also a moral struggle over legitimacy, responsibility, and urban belonging. Residents’ everyday ethical dilemmas, we suggest, are shaped by these broader discursive battles over what a good neighborhood ought to be.
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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 | 0.019 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.034 | 0.162 |
| Scholarly communication | 0.015 | 0.008 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".