Victoria's suburban sprawl as a barrier to sustainable development
Bibliographic record
Abstract
Canada is a nation where over two thirds of the population lives in some form of suburb (Gordon & Janzen 2013). It is important to monitor the locations of population growth within our nation as it has profound effects on our economic effectiveness, environmental sustainability, and our overall public health. The purpose of this study is to estimate Victoria’s 2016 suburban population using housing density and journey-to-work transportation data to classify the Census Metropolitan Area (CMA) into exurban, auto suburb, transit suburb, or active core. Using Transportation Method 9 (Gordon 2018), it was found that 74.9% of Victoria’s population lived in suburban settings in 2016, with 65.3% situated in auto suburbs at the time of the 2016 census. Victoria had Canada’s highest active transportation average at 16.9%, with the second highest being Kingston at 9.5%. The population living in Victoria’s active cores was 21%, a 4% increase from 2011 with only 17% active core.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".