Strategies for Managing Work/Life Interaction among Women and Men with Variable and Unpredictable Work Hours in Retail Sales in Québec, Canada
Bibliographic record
Abstract
Increasingly, work schedules in retail sales are generated by software that takes into account variations in predicted sales. The resulting variable and unpredictable schedules require employees to be available, unpaid, over extended periods. At the request of a union, we studied schedule preferences in a retail chain in Québec using observations, interviews, and questionnaires. Shift start times had varied on average by four hours over the previous week; 83 percent had worked at least one day the previous weekend. Difficulties with work/life balance were associated with schedules and, among women, with family responsibilities. Most workers wanted: more advance notice; early shifts; regular schedules; two days off in sequence; and weekends off. Choices varied, so software could be adapted to take preferences into account. Also, employers could give better advance notice and establish systems for shift exchanges. Governments could limit store hours and schedule variability while prolonging the minimum sequential duration of leave per week.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".