Bibliographic record
Abstract
Introduction: Time-use research is a useful approach to examine the health impacts of how people spend their time and the factors that influence their time. One such factor is gender. Aim: This study undertakes a scoping review to map and synthesize recent research done on the interrelationships among gender, time-use, and health. Design: Web of Science and PubMed electronic databases were searched to identify research published between 2015 and 2020. Forty-four studies that met the eligibility criteria were selected. Results: Most studies on the topic are quantitative in nature, focus on developed country contexts, and have mental health and nutrition as thematic health focus. There is diversity in the kinds of population being studied, with an increasing focus on children and adolescent populations. Conceptual findings reveal multi-directional and life-course aspects of the relationship; point that the relationship between time-use and health varies by the stage of the epidemiological and the nutrition transition; and highlight the need to study the health and well-being impacts of gendered caregiving. Conclusion: This review highlights the need to conduct qualitative studies, give attention to health outcomes such as chronic illnesses, occupational health issues, and physical pain, and increase research focus on developing country contexts where gender inequality in time-use and health is severe.
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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 | 0.009 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.014 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".