Gender Differences in Activity Participation, Time-of-Day, and Duration Choices: New Evidences from Calgary
Bibliographic record
Abstract
Women have been an increasingly important part of Canadian labor force since 1950s. However, it has been argued that they still play very different roles than men in our households and society. A literature review indicates that only limited research quantified the differences of female and male activity patterns, and analyses at individual activity level are scarce. Past research has focused on investigating the gender's differences in their mobility level based on the observed travel patterns, especially those related to commuting travel. This paper reports new evidences based on the analyses applied to the household activity survey (HAS) dataset collected in 2001 in Calgary, Canada. Study results show that contemporary females and males have a very similar activity participation pattern. On the other hand, analyses applied to activity starting time support that there are minor gender differences in time-of-day choices. In addition, duration statistics and survival analyses show that women and men tend to spend more or less time on certain activities, and thus indicate that they share different domestic and societal responsibilities. It is found that males tend to spend longer time for out-of-home activities, such as work, school, sociality, and out-of-town; whereas females contribute more to domestic works, including shopping, eating, and religious. In general, this paper contributes new evidences to gender differences in activity participation, time-of-day and duration choices at individual activity level. Such differences may influence travelers' time, mode, and location choices and thus have important implications to an activity-based modeling framework.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".