Urban rapid rail transit and gentrification in Canadian urban centres: A survival analysis approach
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Despite the existing knowledge that urban rapid rail transit has many effects on surrounding areas, and despite some attempts to understand the links between transit and gentrification, there remain methodological gaps in the research. This study addresses the relationship between the implementation of urban rapid rail transit and gentrification, which is conceived of as an event. As such, an event analysis approach using ‘survival analysis’ is adopted as the statistical analytical tool. It tests whether proximity to rail transit is related to the onset of gentrification in census tracts in Canada’s largest cities. It is found that proximity to rail transit, and to other gentrifying census tracts, have a statistically significant effect on gentrification in two of the three cities analysed. By providing a methodological framework for the empirical analysis of the impact of urban rail transit on gentrification, this paper is a reference for both researchers and transportation planners.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it