Homeworking, telecommuting and journey to workplaces - Are differences among genders and professions varying over space?
Bibliographic record
Abstract
The aim of this paper is to assess differences on homeworking and teleworking behaviour among genders considering age groups, professional statuses, household structures and car access. The analysis is based on a sample of more than 30,000 workers responding to the 2001 origin-destination (O-D) survey data in Quebec City (Canada). Moreover, this paper puts specific emphasis on linking those differences in behaviour to the location of workplaces related to living places of the respondents. During the O-D survey, every worker was asked to disclose the frequency of homeworking and teleworking he/she was experiencing during the preceding weeks. Answers were later aggregated into six categories: never working at home (88.4% of respondents), working at home 1 day per two weeks or less (4.8%), 1 day per week (1.7%), 2 or 3 days per week (1.2%), 4 days or more per week (0.7%), always working at home (3.2% – homeworkers). However, those patterns show significant differences among genders (higher proportion of females are working entirely at home; higher proportion of males are occasionally working at home), age groups (younger workers seldom work at home and the proportion of teleworker increases with age – about 16% among the 55-64 years old and 27% among the elderly) and professional status (proportion of teleworkers is strongly related to qualifications and decisional status of the person, yielding higher levels of teleworking for managers, self-employed persons, professors and lawyers than for office clerks, technicians and non-qualified workers). This last relationship is very strong suggesting that job empowerment (especially ability to control time schedule) is of paramount importance for the development of teleworking. However, having higher family constraints, lone parents are seeking more flexibility on their work agenda: 12% are experiencing some level of teleworking on top of 3% of them which are homeworkers. Again, the difference appears more significant among male than among female workers, suggesting again a better control of the first group on their work schedule. Moreover, owning a driver license or holding a bus pass does not have the expected effect on teleworking: car drivers are working at home more frequently than other people; conversely 92% of bus users are going to their work place every weekday, leaving a mere 8% to teleworking and homeworking. Significant differences appear when considering workplaces and home locations within the city. People working near the city centre are more willing than others to consider teleworking, people living in the suburban areas show higher levels of homeworking. Finally, significant differences of travel time from home to work were found among various categories of teleworkers and homeworkers. Preliminary results suggest that the development of teleworking could be highly rooted to labour market and household structures as well as to the urban form. Urban sprawl is probably impeding development of teleworking, at least for Quebec City.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".