Strategies used by women workers to reconcile family responsibilities with atypical work schedules in the service sector
Bibliographic record
Abstract
OBJECTIVE: Workers' attempts to accommodate family needs may be considered illegitimate in the paid work sphere. Their attempts at work-family balancing (WFB) in that sphere can remain invisible, even when those attempts require considerable energy. Since identification of WFB strategies can potentially lead to suggestions to improve management practices, we report an attempt to find them in the work sphere. PARTICIPANTS: 14 care aides in a Québec residence for seniors and 2~schedule managers were recruited. METHODS: Qualitative ergonomic analysis was employed. 24 hours observation; interviews of nursing and human resources staff; qualitative ergonomic analysis by two researchers; feedback collected from meetings with management and union. Strategies for schedule choice were compared between care aides with heavier vs. lighter family responsibilities. RESULTS: For workers with heavier family responsibilities, choice of work schedules was almost entirely conditioned by family considerations, leaving little leeway to manage workers' own health protection. CONCLUSIONS: Family constraints affected activity at work, and strategies for handling family constraints could potentially be affected by changes in work organization. Managers should encourage full discussion of work-family balancing strategies if they wish to adapt their working conditions to the workers, and ergonomists should include this balancing as a facet of work activity, despite possible negative consequences.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".