How common is greening in gentrifying areas?
Bibliographic record
Abstract
Green gentrification occurs when urban greening/sustainability interventions become implicated in neighbourhood upgrading and displacement of existing residents. However, current emphasis on urban sustainability in planning/policy agendas, coupled with political-economic factors producing uneven development, lead us to ask whether all gentrifying areas experience greening. Our descriptive analysis identified gentrifying areas in Vancouver, Calgary, and Toronto (Canada), from 1996–2006 and 2006–2016, and determined the extent to which various greening interventions (parks, cycle lanes, community gardens, LEED-certified buildings, and rapid-rail transit) were introduced before, during, and after gentrification. Greening frequently occurred before and/or during, and after, gentrification. Our results indicate greening is common in gentrifying areas throughout the gentrification process, suggesting the need for a broader understanding of the relationship(s) between urban greening and gentrification. We outline a future research agenda to examine greening across gentrifying areas and further understand how these two processes shape each other in the remaking of neighborhoods/cities.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".