For a Greater Region: How Has Rail Coverage Changed in the Greater Toronto & Hamilton Area?
Bibliographic record
Abstract
The population of Toronto and the surrounding municipalities in the Greater Toronto and Hamilton Area (GTHA) has been growing with time, and so the transit network should grow accordingly. As such, the growth of the rail transit network in this area of Canada was investigated to determine how the population near rail stops changed over time as a proportion of total population. It was found that, within Toronto, residents within 800m of a rail stop grew from 29% to 34% from 1986 to 2021. However, in the same timeframe outside of Toronto, the GTHA population proportion within 800m of a rail stop stayed steady at 4%. Policy was found to focus on rail, not bus service, and to treat Toronto as a separate planning problem needing different transit solutions than the rest of the GTHA. Because of the low population densities in the municipalities around Toronto, bus transit should be embraced more than it currently is in order to facilitate efficient use of the regional and local transportation systems. Metrolinx, the regional transit provider, should work to improve coverage using collaborations with local municipalities and its own bus network, especially in the context of the planned increased frequency of trains on its rail lines.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".