The Effect of Proximity to Urban Rail on Housing Prices in Ottawa
Bibliographic record
Abstract
Increasingly, urban rail transit (URT) is seen as a desirable solution for transportation challenges faced by both urban planners and residents of suburban areas alike. The availability and ease of access to URT, in turn, may result in distortions in local real estate markets. The conventional wisdom, in fact, suggests that construction of urban rail lines serves as a magnet for new housing development and, in turn, can lead to increases in property values in proximity to URT stations. Existing studies have, in good measure, confirmed this belief, but largely on the basis of global area studies that can often mask locally differentiating factors affecting housing prices. Using data from the City of Ottawa, this study seeks to move beyond such analyses by using spatial regression and mapping techniques that reveal that the relationship between URT stations and housing prices is far more complex than is commonly believed. The study demonstrates that while at the macro-level housing prices do vary positively with proximity to URT stations, the relationship is spatially dependent and may be affected by factors unique to specific locales.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 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".