Modelling changes in accessibility and property values associated with the King Street Transit Priority Corridor project in Toronto
Bibliographic record
Abstract
Despite several decades of research, the relationship between transit accessibility and land values remains unclear. In practice, most research has focused on simple measures of proximity that, while easy to understand, fail to capture the potential for interaction using the transit network. Through the example of the King Street Transit Priority Corridor project, this research examines how transit accessibility, and changes in access over time that result from streetcar service upgrades, are capitalized into condominium prices in Toronto, Canada. Methodological and applied contributions include calculating streetcar travel time differences using disaggregate vehicle tracking data, calculating transit accessibility using a gravity-based measure with a calibrated impedance function, accounting for variations in accessibility over the course of a day as well as changes over time, incorporating measures of access to local amenities, transforming 2D transaction information to a 3D format, and specifying 4D spatio-temporal weights. Longitudinal model results indicate that transit accessibility is a significant determinant of condominium prices. While the service upgrades did not dramatically increase accessibility levels and the implicit value of accessibility did not change over time, panel model results find that condominium property prices appreciated by about 2.7% more on average in the King Street streetcar corridor relative to the Sheppard subway control after the introduction of the priority corridor pilot . This result suggests the corridor on the whole may have became more attractive relative to Sheppard in the pilot phase.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".