Simulating Sustainable Urban Gateway Development
Bibliographic record
Abstract
The term “gateway” refers to a city, or to some transport and logistics-oriented area in a city, that is associated with goods movement in, out, and through the area. Although the definition of a gateway is typically focused on goods movement, a more holistic view is adopted with consideration of the movements of people and the environmental implications of all movements. The relevance of this view is based on the interdependence of commercial and persons mobility, because all moves are happening within the same transport network, and is based on considerations of quality of life in a gateway city. Hamilton, Ontario, Canada, was chosen to test these concepts. Hamilton had a suitable geographical location, a busy port, an international airport, good highway and railway access, and an educated labor force. The gateway prospects for Hamilton were given perspective through a study of other prominent gateways that distilled success factors. Analytical work focused on multiregional economic impact modeling to assess the direct and indirect effects of Hamilton's potential evolution as a gateway. Local-level analysis, through integrated urban modeling and simulation of scenarios, stressed the impact of gateway development on commercial goods movement, auto commuting levels, emission levels, and transit ridership. Increased emissions resulting from gateway economic development could be overcome with forward-thinking policy focused on the uncongested movement of goods and people, compact urban form, and enhanced public transit working in concert. The addition of light rail transit in Hamilton and the promotion of a compact urban form would be catalysts for sustainable local gateway development. Finally, gateway-oriented development in Hamilton will cause noticeable regional economic growth. The models that were developed can be calibrated for other cities, given appropriate data.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".