Route Preferences among Adults in the near Market for Bicycling: Findings of the Cycling in Cities Study
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
PURPOSE: To provide evidence about the types of transportation infrastructure that support bicycling. DESIGN: Population-based survey with pictures to depict 16 route types. SETTING: Metro Vancouver, Canada. SUBJECTS: 1402 adult current and potential cyclists, i.e., the "near market" for cycling (representing 31% of the population). MEASURES: Preference scores for each infrastructure type (scale from -1, very unlikely to use, to +1, very likely to use); current frequency of use of each infrastructure type (mean number of times/y). ANALYSES: Descriptive statistics across demographic segments; multiple linear regression. RESULTS: Most respondents were likely or very likely to choose to cycle on the following broad route categories: off-street paths (71%-85% of respondents); physically separated routes next to major roads (71%); and residential routes (48%-65%). Rural roads (21%-49%) and routes on major streets (16%-52%) were least likely to be chosen. Within the broad categories, routes with traffic calming, bike lanes, paved surfaces, and no on-street parking were preferred, resulting in increases in likelihood of choosing the route from 12% to 37%. Findings indicate a marked disparity between preferred cycling infrastructure and the route types that were currently available and commonly used. CONCLUSION: This study provides evidence for urban planners about bicycling infrastructure designs that could lead to an increase in active transportation.
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 | 0.007 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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