Bibliographic record
Abstract
As commuting distances increase, efficient, effective transit service becomes increasingly important. In order to make transit efficient and increase ridership, we must reconsider how cities and towns grow. Concentrating densities and a mix of uses in and around transit stops and stations is necessary to place more people close to transit at both ends of their trip. The Ontario Ministry of Transportation has developed the Ontario Transit-Supportive Guidelines to support continued progress in building more compact, transit-supportive communities. The Guidelines bring together the most current thinking on transit-supportive urban planning and design and best practices in transit planning and delivery of customer-oriented transit service. The document emphasizes the inter-dependent relationship between transit ridership and land use patterns: that higher density communities need dependable transit systems to thrive, and in turn, transit systems rely on transit-supportive land uses to sustain and increase ridership. The Transit-Supportive Guidelines were released as draft in January 2011, completed later in 2011 and published, following translation and accessible formatting, in January 2012. The Guidelines include over 50 guidelines and almost 450 strategies, with detailed guidance to assist communities of all sizes in promoting development patterns that make transit less expensive, less circuitous and more convenient. The Guidelines also include, for the first time, strategies to enhance the service and operational characteristics of transit systems to make them more attractive to potential transit users through a range of tools, management approaches and technologies. This project was nominated fo rthe TAC 2011 Sustainable Urban Transportation Award. For the covering abstract of this conference see ITRD record number 201211RT334E.
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.
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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.145 | 0.062 |
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".