Bibliographic record
Abstract
Rapid recent growth in the popularity of electric bicycles (e-bikes) has captured the attention of transportation researchers and policymakers seeking safe, sustainable, and active alternatives to conventional transportation modes. This thesis presents an investigation of e-bike owners in North America, complementing previous efforts in 2013 and 2017, and suggests implications for North American transportation planning. An online survey was distributed to e-bike owners in the United States and Canada through email outreach, purchase incentive programs, and social media. The survey included questions on the respondents’ demographics, e-bikes, purchase decisions, travel behavior, perceptions of e-bikes, crash experience, maintenance needs, and receipt of purchase incentives. Owners generally have a positive impression of e-bikes and their benefits. The market continues to be dominated by white, male, and affluent riders, but there is a higher share of women than in previous years. Young and old respondents have taken on the technology for differing reasons: transportation and recreation, respectively. There is some indication that the e-bike market is exiting the early adopter phase; however, the demographic profiles of e-bike riders still differ heavily from the general population. E-bikes are used primarily for utilitarian trips. Their proven ability to offset vehicle miles traveled supports investment in incentives and infrastructure from governments of all levels pursuing climate, health, and transportation equity goals. In particular, targeted initiatives aimed at addressing specific demographic segments and geographical contexts may foster more equitable uptake. Riders expressed a desire to ride their e-bikes more often, and for dedicated infrastructure and secure parking facilities. Few households with children allowed them to ride e-bikes. Respondents demonstrated a general misunderstanding of their e-bikes’ class and capabilities. Improper disposal of e-bike batteries does not seem to be a major concern.
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.
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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".