Non-stop equity: Assessing daily intersections between transit accessibility and social disparity across the Greater Toronto and Hamilton Area (GTHA)
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
Public transportation systems generate economic benefits that can potentially reduce social disparities between populations when such benefits are distributed evenly within a region. However, the achievement of equity in the allocation of public resources is not easy to accomplish for land use and transportation planning agencies. This research seeks to determine whether people residing in socially disadvantaged areas in the Greater Toronto and Hamilton Area (GTHA), Canada, experience the same levels of transit accessibility as those living in other areas over the course of a day. Comparisons are presented in terms of regional accessibility, trends by social decile, spatial distribution of accessibility during the day, and travel time impacts. Findings suggest that residents in socially disadvantaged areas have equitable if not better transit accessibility to jobs than socially advantaged groups, and this is reflected in shorter travel times. However, the degree and impact of this advantage varies over the course of the day. Findings from this research can be of interest to transportation planners, engineers, and policy makers as it highlights deficiencies with current equity assessment practices that do not take into account variation in transit services over a 24-h time period.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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