Examining working time arrangements using time use survey data
Bibliographic record
Abstract
This paper uses full-record time diary data from six studies conducted in four countries, Canada (1992), the Netherlands (1990 and1995), Norway (1980, 1990), and Sweden (1991), to analyse daily schedules of individual work time patterns.The work schedules are based on the combination of regular paid work, overtime work, second jobs, and any reported informal paid activity.We define work episodes as single occurrences of paid work activity separated by 60 or more minutes from any other paid work episodes.The reference work episode was the one that occurred during "core" hours, which were defined as 8:00 a.m.-6:00 p.m. for Canada and Netherlands, and as 7:00 a.m.-4:00 p.m. for Norway and Sweden.These "core" time definitions were based upon the frequencies of start and end-times of work episodes.Work episodes were calculated for all days, including weekend days.We identified seven theoretical work time arrangements possible during a day for each individual with reference to the core working hours.These classifications of work time arrangements extend from early morning to late night with three classifications being single arrangements and four being multiple and overlapping arrangements.Empirically these arrangements, in combination, generated 10 workday patterns for individuals.We found vast, though as yet statistically untested, differences in work time arrangements across countries and by sex.In general, men tended to be relatively evenly distributed over the work time arrangements defined for a typical day, while women tended to work a single episode during core hours only.2/3 of Canadian and Swedish men worked at least some time outside core hours, while nearly half of Dutch and Norwegian men only worked during the core period.Women in Sweden worked a wider range of hours than women in the other three countries.Where possible, this paper explores relations between other aspects of working arrangements and the timing of paid work episodes.We found a strong relationship between the scheduling and the duration of paid work.People who worked both pre-core to core and core to post-core episodes worked the longest hours, while people working post-core only or only working core to post-core episodes put in the fewest hours.
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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 | 0.016 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.015 |
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; both teacher heads agree on what is shown here.
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".