Generational Differences in Trip Timing and Purpose: Evidence from Canada
Bibliographic record
Abstract
Abstract Recent anecdotal evidence suggests that millennials (individuals born following Generation X and between the early 1980s and early 2000s) are characterized by different travel behavior characteristics, including being less likely to have a valid driver's license and less likely to drive than their older counterparts. The old, conversely, represent a rapidly growing segment of the Canadian population that have grown up with the personal automobile and are dependent on it. But are there differences in trip purpose and timing between different generational cohorts? Using data from Statistics Canada's 2010 General Social Survey “Time Use” cycle, this paper evaluates the purpose and timing of trips across generational cohorts, with the paper distinguishing between millennials, generation X, baby boomers, and the greatest generation. Descriptive statistics are used to characterize the purpose and timing of trips, and multivariate analyses of peak versus non‐peak departure‐time models offers insights into the differences and similarities across cohorts. Findings suggest that the timing of travel, along with reasons for travel, are broadly similar across the generations.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 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) | 0.003 | 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".