Revealed Choice of a New Generation: Travel Behavior of Older Drivers in Rural New Brunswick, Canada
Bibliographic record
Abstract
The effects of aging, in concert with high automobile dependence due to limited alternatives, means rural older people are particularly vulnerable to losing automobile-related mobility with age. The development of successful alternatives requires replicating the conditions that make car use attractive which begins with enhancing the understanding of how current rural older drivers use their cars. Detailed travel information from Global Positioning System (GPS)-based travel diaries, supported by participant stated responses can lead to a better understanding of these conditions at a level not typically explored for this group. This paper profiles the travel behaviour of a convenience sample of 60 drivers (average age 69.6 years) in rural New Brunswick, Canada collected through GPS-based travel diaries and participant-supplied contextual information. Participants completed an average of 4.29 driving trips per day and 1.06 passenger trips per day in their own vehicles, while travelling in 81% of all eligible survey days. The proportion of passenger trips taken in one’s own vehicle increased with age for men and decreased for women, and was equivalent for men and women aged 75 years and older. “Higher Order/Serving Others” and “Life Maintenance” trip purposes comprised 55% and 45% of all trips, respectively. Participants completed 67% of “shopping” trips and 72% of “medical” trips in urban areas with 76% of “social” trips in rural areas. Rural participants were able to meet many of their life maintenance and higher order needs in rural areas, suggesting that transportation access to urban areas cannot be the sole impetus of transportation policy for non-drivers.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".