Alleys for whom? The Socioeconomic dimensions of green alleys in Verdun, Montreal, Canada
Bibliographic record
Abstract
The green alley (ruelle verte) programme is an urban greening initiative in which Montréal residents collaborate with the local branch of a non-governmental organisation and their municipal government to transform their back alley into a greened space for community gathering and activities.However, since people from different socioeconomic groups may have unequal access to resources, urban greening initiatives do not always benefit everyone equally.Therefore, one may wonder: who are green alleys truly for?My thesis aims to answer this question in the context of Verdun, a lower-to-true middle class, gentrifying borough of Montréal.Through my triangulated methods of green alley audits, resident questionnaires and resident and key informant interviews, I determine alley quality is not related to household income, that socioeconomic groups seem to have some differing experiences and challenges with the programme, and that alley quality appears to shape resident opinions of and experiences with their green alleys.
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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 | 0.008 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".