A Methodology to Quantify Discontinuities in a Cycling Network – Case Study in Montréal Boroughs
Bibliographic record
Abstract
Many studies have investigated the cause of the low mode share for active modes of transportation, walking and cycling, in North America. Since the primary purpose of any transportation network is to provide connectivity between the origin and travel destination, studies have considered the discontinuities in the cycling facility as a major reason for lower cycling mode shares. Network connectivity decreases travel distances and provides a set of possible routes that are easily accessible for all road users. On the other hand, discontinuities correspond to points in the network were the cycling network is not connected and a cyclist may have to reconsider his/her route and will be more exposed to motorized traffic. This paper proposes a methodology to identify and quantify discontinuity within a cycling network using geospatial data and a geographic information system. This study identified two types of indicators, A) internal cycling network discontinuity indicators: the number of ends of bike facilities, the changes in bike facility type, and B) discontinuity indicators with respect to the road network: the number of intersections on bike facilities, the variations in the number of lanes, road type, motorized traffic volume along bike facilities and the number of bus stops on bike facilities. The dataset and step-by-step process of quantifying these discontinuity measures are presented and applied to three boroughs in the island of Montreal for comparison.
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How this classification was reachedexpand
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 | 0.033 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".