Bloor Bike Lanes: Assessing The Economic Impact Of Bike Lanes In The Planning Of A 21st Century Street
Bibliographic record
Abstract
Cycling and cycling-specific infrastructure are timely topics that addresses the mounting need for an improved and sustainable transportation network in Canadian cities (Litman & Burwell, 2006). The accompanying need for increased regulation and appropriate space in the public realm has resulted in cyclists gaining their right to access public space through the installation of bike lanes in cities like Toronto (Ellison, 2013). In 2016, the City of Toronto adopted the Cycling Network Ten Year Plan (hereafter: the Plan), a comprehensive roadmap directing the city towards a bicycle-friendly transportation grid. The Plan represents Toronto’s commitment to building an integrated transportation network serving the needs of cyclists. The Plan’s mandate is trifold: connect the gaps in the existing cycling network, grow the cycling network, and renew the quality of existing cycling routes (City of Toronto Transportation Services, 2016b). In addition, in 2016, Toronto City Council approved the Bloor Street Bike Lane Pilot Project, a one-year project along a major transportation corridor that includes Line 2 of the city’s subway line. The Bloor Street Bike Lane Pilot is identified as a priority corridor in the Plan. As part of the evaluation, a major corridor study will assess the implementation of cycling-specific infrastructure across Bloor Street (City of Toronto Transportation Services, 2016a).The City of Toronto Transportation Services will present the Bloor Pilot Bike Lanes Evaluation Report to City Council in Fall 2017; the evaluation report will in part assess the economic impact of bike lanes on the study corridor. While there is a growing base of grey literature that demonstrates the relationship between cyclists, bike lanes, and economic vitality, it is not as well documented in the academic literature. Bloor Bike Lanes: assessing the economic impact of bike lanes in the planning of a 21st Century Street synthesizes interdisciplinary research, exploring the role of bike lanes in a changing urban landscape through the context of Bloor Street.This report speaks to a growing trend in bicycle ridership (Mitra et al., 2016) and acknowledges the value of bike lanes to the contemporary city. In Toronto’s planning of a street network that facilitates movement, growth, dynamism, and interaction among diverse road users, this report contributes to this discussion by articulating the importance of bicycle-friendly streets. This is the primary objective of this report. The Toronto Centre for Active Transportation (TCAT) in collaboration with the Toronto Cycling Think & Do Tank at the University of Toronto, have partnered to undertake a study evaluating the economic impacts of the Bloor Street bike lanes on local business (2015). This report speaks to their work by synthesizing existing and recent literature about the economic vitality associated with bike lanes.
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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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".