CommunoSerre: Issues facing urban community greenhousesin disadvantaged neighborhoods - A toolkit for practioners and decision-makers
Bibliographic record
Abstract
The objectives of the research project were to examine the technical, socioeconomic and political challenges associated with urban community greenhouses’ integration, particularly in Montreal's disadvantaged neighborhoods. More specifically, the research team examined the potential of geothermal technologies, water management strategies and various greenhouse designs to improve their energy efficiency performance in Quebec's harsh climate. A greenhouse gas emissions calculator was developed to inform decision-making on how to reduce the ecological footprint of urban community greenhouses with technologies adapted to community groups and urban realities. The team also analyzed the socioeconomic and political issues arising from the motivations driving community greenhouse projects, as well as the partnerships and financing required to make them a reality. Inclusive measures deployed by project leaders are also identified to reach a diversity of Montrealers, particularly the most vulnerable, and address the risks of ecogentrification associated with greenhouses. This toolkit explores the sociopolitical issues at stake and proposes technical recommendations to consider when planning an urban community greenhouse.
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".