New Insights into Senior Travel Behavior: The Canadian Experience
Bibliographic record
Abstract
ABSTRACT Societies in many developed nations around the world are aging. Over the past decade, a growing body of research has emerged internationally in an effort to anticipate and prepare for the transport challenges posed by this unprecedented demographic change. This paper contributes to this line of research by offering new insights into senior travel behavior focusing on the recent Canadian experience. Using weekday data from the 1992 and 2005 General Social Surveys on time use, changes in the number of trips, the duration of trips, trip mode, and trip timing are evaluated for urban seniors. In contrast to the experiences of many other developed nations, analysis of the first three indicators of behavioral change refutes the notion that “automobility” has increased in Canada over the 13‐year period. While this finding is encouraging, it is tempered by the fact that Canadian seniors who choose to travel by car are doing so increasingly during the morning and evening peak periods. The results from a peak versus non‐peak departure‐time model that pools data from both years offer important insights into factors driving this change. For instance, the results suggest that the propensity to start a trip during rush hour has increased over time for non‐work trip purposes.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".