Easy as riding a bike? Bicycling competence as (re)learning to negotiate space
Bibliographic record
Abstract
Safety concerns, notably sharing road space with motor traffic, pose barriers for bicycling. To address safety concerns, bicycle courses are designed to provide skills and know-how for bicyclists to share road space with traffic. This paper used Social Practice Theory combined with a critical gender lens to examine the impact of a bicycle course for women living in Vancouver, Canada. We aimed to: 1) describe bicycling competences and associated materials and meanings; 2) compare bicycling competences at different stages of uptake and maintenance; and 3) identify gendering processes shaping bicycling practices. We conducted interviews with 32 women in the year following their participation in a bicycle course. Data collection and analysis were guided by interpretive description methodology. Participants described competences as skills for road positioning and route-finding, knowing formal and informal rules (laws, etiquette) to interact with other road users, and having strategies to minimise gender harassment. Regarding uptake and maintenance, women with opportunities to engage in bicycling cultivated competences more quickly. Those without suitable bicycles rarely rode; others described a virtuous circle where more time in the saddle led to greater confidence. Gendering processes shaped nearly all aspects of bicycling and included safekeeping (taking disproportionate personal responsibility for safety) and cultivating an assertive bodily comportment to take up space. We recommend that courses be augmented with support to acquire suitable bicycles, social opportunities for bicycling, continued investment in bicycle infrastructure, education for motorists, and discussion regarding etiquette between bicyclists.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".