Shaping Vancouver 2016: Our Neighbourhoods - What Do I Want From My Street?
Bibliographic record
Abstract
In this panel, speakers discuss the impact of Transit Oriented Development (TOD) along some of our prominent North South arterial streets – Cambie, Main, Fraser, and the communities along them.\nIncreasingly, we see the character and street level retail disrupted by the creation of high-density mixed-use areas close to public transport. Although this kind of development increases the housing supply, questions around diversity, density distribution, community assets, and neighbourhood quality remain. It is a model that appears to preserve low-density single-family neighbourhoods by introducing Metrotown like developments.\nIs this the best way for Vancouver to address the development imperatives it is facing and if the preservation of low-density single family areas justify the creation of high density nodes?\nThe panel will explore what factors make a street work, including how accessible it is for various modes of transportation, how it allows for a variety of activities, how pedestrian oriented it is, whether it provides comfortable gathering spaces, and how it contributes to a distinct image of its neighbourhoods as a means to assess the impact of the TOD development being proposed for Vancouver. A general discussion with the audience follows at the end.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.003 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.044 | 0.007 |
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".