What type of person is at different stages of change for cycling? A case study of Montreal
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
Promoting cycling for daily transport has significant health, equity, and environmental benefits. To understand what factors influence individuals’ cycling motivational stages, our study pursued two main objectives: 1) Enhancing the Stage Model of Self-Regulated Behavioral Change (SSBC) by integrating it with the psychological mechanisms of the TPB, and 2) Examining the impacts of perceived cycling motivators and barriers, cycling and general attitudes, and sociodemographics on cycling motivational stage. Using an online survey of the adult population (n = 1055) in Montreal, Canada, a multivariate analysis reveals meaningful connections between behaviour stages and perceived barriers and attitudes toward cycling. Those in the lowest stage exhibit lower internal motivation and express concerns about the lack of convenience, physical effort, and slowness associated with cycling. Furthermore, the results challenge the common understanding that people always progress through the stages with increasingly positive attitudes and more cycling. Specifically, our findings highlight the need to distinguish between people who cycle by choice and those who do so out of necessity (i.e., captive riders) when categorizing travelers into action and post-action stages. This is important due to the risk of people in the “captive action stage” going back to using cars if barriers are reduced. This suggests that intervention policies should also focus on current cyclists, not just non-cyclists of the preaction stages. This nuanced understanding can inform more effective and targeted interventions for promoting cycling. Finally, objective characteristics of cycling infrastructure retains significance in explaining who belongs to the postaction stage for cycling, even after controlling for residential self-selection.
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 | 0.000 | 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