Gentrification, perceptions of neighborhood change, and mental health in Montréal, Québec
Bibliographic record
Abstract
While census-defined measures of gentrification are often used in research on gentrification and health, surveys can be used to better understand how residents perceive neighborhood change, and the implications for mental health. Whether or not gentrification affects mental health may depend on the extent to which an individual perceives changes in their neighborhood. Using health and map-based survey data, collected from 2020 to 2021, from the Interventions, Research, and Action in Cities Team, we examined links between perceptions of neighborhood change, census-defined neighborhood gentrification at participant residential addresses, and mental health among 505 adults living in Montréal. After adjusting for age, gender, race, education, and duration at current residence, greater perceived affordability and more positive feelings about neighborhood changes were associated with better mental health, as measured by the mental health component of the short-form health survey. Residents who perceived more change to the social environment had lower mental health scores, after adjusting individual covariates. Census-defined gentrification was not significantly associated with mental health, and perceptions of neighborhood change did not significantly modify the effect of gentrification on mental health. Utilizing survey tools can help researchers understand the role that perceptions of neighborhood change play in the understanding how neighborhood change impacts mental health.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".