When I’m 64: Assessing Generational Differences in Public Transit Use of Seniors in Montreal, Quebec, Canada
Bibliographic record
Abstract
The growth rate of adults older than 65 in Canada is increasing more rapidly than the population as a whole. This increase is reflective of the aging baby boomer population. That population is known to have a strong attachment to automobiles, which might be reflected in their travel behavior as they move toward different stages in their older life. The purpose of this paper is to contribute to the understanding of the travel behavior, mainly public transit usage, of Canada’s older population relative to younger cohorts. A pseudocohort analysis was conducted in Montreal, Quebec, Canada, of residents who were 50 or older to follow changes in public transit use of similarly aged respondents from 1998 to 2013. The results revealed that older generations used public transit more than younger generations did at the same age. In addition, the most recent survey year showed a stagnation of transit use across all age groups. Differences in transit use between males and females were more pronounced in earlier cohorts, but the difference was decreasing in more recent years. These findings add to the growing body of work suggesting that the nature of transportation behavior in seniors is changing, and accordingly planners and engineers cannot expect the baby boomer generation to behave the same way as previous generations. Addressing the transportation needs of seniors around the world will be an important challenge for planners and engineers, as the population of seniors is growing more rapidly than the population as a whole in the majority of developed countries. This growth imposes new challenges on the transportation system because of differences in the travel behavior of today’s older adults compared with that of previous cohorts of seniors.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".