A Comparative Analysis of Transportation Systems in Kamloops and Vancouver: The effects on the environment and sustainable living
Bibliographic record
Abstract
Transportation systems shape urban sustainability, health, and everyday life. This study compares Vancouver and Kamloops, B.C., to assess how infrastructure influences travel behavior and per-capita transportation emissions. Using publicly available government data, planning documents, statistical records, and prior studies, supplemented by lived experience, we analyze mode shares, transit accessibility, walkability, and emission profiles. Vancouver’s integrated network of frequent transit, protected cycling routes, and transit-oriented neighbourhoods corresponds to lower transportation emissions at 39 percent and higher active-mode use of walking and cycling at 29 percent. In Kamloops, car dependence dominates (88% of trips), and transportation contributes a larger share of emissions at 66 pc. Kamloops' fragmented walkability and topographic constraints further limit alternatives. While geographic and environmental factors preclude a simple replication of Vancouver’s model, targeted improvements in Kamloops—such as enhanced bus frequency and coverage, connected and protected cycling infrastructure, and walkable, mixed-use neighbourhood design—could deliver meaningful reductions in emissions and co-benefits for public health and social inclusion. The findings highlight that even in car-dependent mid-sized cities, incremental, context-sensitive interventions in sustainable transport can yield outsized gains. Keywords: sustainable transport, mode share, transit accessibility, walkability, per-capita emissions, mid-sized cities
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".