Densification of Vancouver's neighbourhoods: Energy use, emissions, and affordability
Bibliographic record
Abstract
The City of Vancouver in British Columbia has committed to use 100% renewable energy and reduce emissions by 80% by 2050.Like many cities in North America, much of the Vancouver's land area currently consists of single-family detached home neighbourhoods-a type of land use that has been associated with higher than average per capita energy use and emissions.In this study, I used an energy-economyemissions model, CIMS, to evaluate how densifying these low-density neighbourhoods with medium-density housing forms would influence energy use, emissions, and home energy and personal transportation affordability.While densification was found to have a modest influence on reducing building emissions, zero-emission building regulations were found to be much more effective, highlighting the importance of energy-switching policy for residential building decarbonization.However, an affordability co-benefit of densification was found: smaller, more energy efficient dwellings in dense building forms reduce annual energy costs relative to detached homes, especially when coordinated with policies and actions to limit vehicle ownership.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".