Why Not Bike? : Exploring the Cycling Behaviours of UBC Cyclists
Bibliographic record
Abstract
The University of British Columbia (UBC) sees over 76,000 trips to and from its campus on a daily basis. These trips occur through many means of transportation, ranging from personal vehicles, public transportation, cycling, and walking, to name a few. Despite the city of Vancouver and UBC’s efforts to improve infrastructure and interest, minimal improvements have been made regarding the percentage of those who cycle to campus. Within this group is an even smaller community of those who cycle regularly (2-5 times a week), leading most to cycle infrequently, or irregularly (less than twice a week). Past research has identified barriers such as perceived safety, confidence, and experience of the cyclists being reason to their infrequency (Kelarestaghi, Ermagun, & Heaslip, 2019). The goal of this study is to identify the cycling behaviours of UBC commuter cyclists and to determine the barriers that prevent more commuters, specifically irregular cyclists, from increasing their cycling frequency. We also aim to provide insight to UBC and other relevant organizations, governments, and stakeholders involved in the cycling community to improve cycling infrastructure and promotion. The online platform ‘Qualtrics’ was utilized to create an online survey consisting of multiple choice and fill-in-the-blank questions to allow a wide distribution to many UBC students, faculty, and staff. The questions included in the survey evaluated sociodemographic factors of the respondents as well as more specific questions regarding their cycling habits and improvements they would like to see regarding cycling infrastructure and promotion. The incentive of a gift card prize draw was provided to increase interest. In total we received 88 responses with only one response from a non-student, which led us to discard that singular response to improve consistency. Correlation between opinions and age/gender were found, as well as consistency among cyclists and non-cyclists regarding their views on factors such as barriers and required improvements. The largest barriers identified by the group were not having a functional bicycle, distance from their residence to campus, and adverse weather the city of Vancouver faces. The majority of respondents had no experience cycling to campus. Lack of bicycle ownership was an issue in this instance. Within the group that did cycle to campus, barriers to cycle more frequently included personal safety such as feelings of safety although no further detail was provided. Major limitations of the study include sampling bias and providing more in depth questions to explain behaviour. The study was not distributed widely enough to receive responses from individuals from a variety of different sectors of UBC meaning that our sample is not representative of the population. Furthermore, although our questions were descriptive they did not provide enough detail to explain behaviour of respondents such as why males felt more unsafe cycling than females. Our recommendations include providing education to cyclists to improve their confidence and feelings of safety and providing monetary incentives to increase interest in cycling. Regarding our research process, adjusting our survey to provide more specific questions to irregular cyclists to explain their behaviours and accessing a more representative population of UBC would be recommendations. Disclaimer: “UBC SEEDS provides students with the opportunity to share the findings of their studies, as well as their opinions, conclusions and recommendations with the UBC community. The reader should bear in mind that this is a student project/report and is not an official document of UBC. Furthermore readers should bear in mind that these reports may not reflect the current status of activities at UBC. We urge you to contact the research persons mentioned in a report or the SEEDS Coordinator about the current status of the subject matter of a project/report.”
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".