Environmental and demographic correlates of bicycling
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
OBJECTIVE: The present study examined correlates of bicycle ownership and bicycling frequency, and projected increases in cycling if perceived safety from cars was improved. METHODS: Participants were 1780 adults aged 20-65 recruited from the Seattle, Washington and Baltimore, Maryland regions (48% female; 25% ethnic/racial minority) and studied in 2002-2005. Bicycling outcomes were assessed by survey. Multivariable models were conducted to examine demographic and built environment correlates of bicycling outcomes. RESULTS: About 71% of the sample owned bicycles, but 60% of those did not report cycling. Among bicycle owners, frequency of riding was greater among young, male, White, educated, and lean subgroups. Neighborhood walkability measures within 1 km were not consistently related to bicycling. For the whole sample, bicycling at least once per week was projected to increase from 9% to 39% if bicycling was safe from cars. Ethnic-racial minority groups and those in the least safe neighborhoods for bicycling had greater projected increases in cycling if safety from traffic was improved. CONCLUSION: Implementing measures to improve bicyclists' safety from cars would primarily benefit racial-ethnic groups who cycle less but have higher rates of chronic diseases, as well as those who currently feel least safe bicycling.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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