It’s snowing? Keep on rolling! Individual determinants of winter cycling in Québec
Bibliographic record
Abstract
Bicycle commuting during the winter is an increasingly popular practice in Québec, Canada, that is associated with benefits for public and environmental health. Constructs of the Theory of Planned Behavior and habit are associated with modes of transport and active commuting. Researchers have not yet examined whether these psychological factors are associated with winter cycling in nordic climates. The aims of the study were to describe winter bicycle users’ socio-demographic and psychological characteristics as well as perceptions of environment and assess whether the Theory of Planned Behavior and habit constructs are longitudinally associated with winter bicycle commuting. A longitudinal design with two online questionnaires was implemented between January-March 2022. The first questionnaire assessed individual variables. Four weeks later, a second questionnaire collected data on the use of winter bicycle commuting in the last seven days. A structural equation model was performed to examine longitudinal associations between psychological constructs and weekly winter cycling. The study included 624 and 487 participants at baseline and follow-up, respectively. Participants mainly identified as men (60%) and mean age was 44 years old. Our results demonstrated that attitudes (β= 0.21; 95%CI [0.06, 0.36]), perceived control (β= 0.92; 95%CI [0.61, 1.12]), intention (β= 0.53; 95%CI [0.39, 0.66]), and habit (β= 1.12; 95%CI [0.60, 1.65]) exhibited significant positive associations with engaging in bicycle commuting during winter. The level of habit had a stronger association with behavior than intention. Findings suggest that future winter cycling intervention should combine behavioral change techniques (targeting attitudes, perceived control, intention, and habit) with winter bicycle-friendly infrastructures and policies.p { margin-bottom: 0.25cm; direction: ltr; color: #000000; line-height: 115%; text-align: left; orphans: 2; widows: 2; background: transparent }p.western { font-family: "Calibri", sans-serif; font-size: 11pt; so-language: fr-CA }p.cjk { font-family: "Calibri"; font-size: 11pt; so-language: en-US }p.ctl { font-family: "Times New Roman"; font-size: 11pt; so-language: ar-SA }a:visited { color: #954f72; text-decoration: underline }a:link { color: #0563c1; text-decoration: underline }
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".