The Effect of International Airports on Commercial Property Values: Case Studies of Toronto, Ontario, Canada and Vancouver, BC, Canada
Bibliographic record
Abstract
Abstract Airports are the portals where international air transport networks, which are increasingly important in a globalized, services-oriented economy, intersect with regional and metropolitan ground transportation networks. Our hypothesis is that, at this nexus, the degree of international connectivity at an airport and distance from the airport manifests itself in the value of commercial properties. As such airports are shaping the urban form around them and highlight the importance of integrated metropolitan and airport planning. Looking at Canada’s two largest international airports at Toronto, Ontario and Vancouver, BC, and controlling for other factors, we see evidence that commercial properties decrease in value as distance to the airport increases and increase in value as the range of international frequencies and destinations available at the airport increase. We introduce a new concept of land-use at and around airports of “aviation-dependent” which would include hotels and corporate head offices, in addition to the traditional “aviation-related” and “aviation-compatible” uses. We see the effects of distance and connectivity are particularly pronounced on commercial properties occupied by aviation-dependent uses.
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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 | 0.001 | 0.008 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".