Estimating walking and bicycling in Canada and their road collision fatality risks: The need for a national household travel survey
Bibliographic record
Abstract
Canada does not conduct a national household travel survey, resulting in a data gap on walking and bicycling. These data are key to surveillance of physical activity and health, as well as in epidemiological injury risk calculations. This study explored the use of available national data sources, the Canadian census and the Canadian Community Health Survey (CCHS), to tally walking and bicycling and examine trends in fatality risk. Estimates of the percentage and number of Canadians walking or bicycling to work were calculated for 1996-2016 using the census. The CCHS was used to estimate the number and proportion of Canadians walking or bicycling for leisure (2000-2014) and to work or school (2008-2014). We combine these data with National Collision Database data on the number of pedestrian and bicyclist fatalities (1999-2017) and compare trends in fatality risk over time using each dataset. Across all data sources, walking was more common among women, while bicycling was more common among men. Men were at higher fatality risk than women. These results should be interpreted with caution given limitations this study identifies in census and CCHS data, including narrow definitions for bicycling behaviour, lack of detail regarding amount of use, and inconsistency of questions asked over time. A national household travel survey should be a priority for public health purposes in Canada.
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How this classification was reachedexpand
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 | 0.005 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".