Exploring the impact of gender in travel behaviour: A case study of suburban commuters in Montreal
Bibliographic record
Abstract
Transportation literature suggests that men and women have different characteristics with respect to commuting patterns, as well as with respect to their propensity to switch between travel options. In North America, women are expected to have an increasing impact on travel demand. As such, differences in female responses to travel demand management strategies are likely to become increasingly important as governments try to curtail travel demand in the future. This paper uses a 1994 stated preference (SP) survey of suburban commuters in Montreal to: determine whether there is evidence for differences between men and women in the factors that affect work trip choices; quantify those differences; and suggest what these differences imply for travel demand management in the future in Montreal. The main conclusions of this paper are as follows. First, women and men should be modeled separately with respect to work trip mode choice. Second, there are three main differences that appear from the econometric models: women are less likely to choose public transit than men; women are more likely to choose to rideshare; and women are less time sensitive when it comes to commuting than men are.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".