How is grocery shopping completed in households with children? Gender gaps and typologies of grocery shopping in four Canadian metropolises
Bibliographic record
Abstract
Grocery shopping is important household labor that directly impacts diet quality and related downstream health outcomes. Like other household tasks, it is usually divided unequally in opposite-gender households, with women doing more grocery shopping than men. However, common indicators used to identify gender gaps, like activity frequency and duration, are unable to sufficiently depict the full picture of the constraints faced by women during grocery shopping activities. This is especially evident for women in households with children, who often share more care-related labor. To address this gap, this paper examined the gender differences in grocery shopping activities across multiple dimensions, including frequency, duration, grocery store types, travel modes, the presence of companions, timing of shopping, and trip chaining. Drawing upon the Time Use & Food Habits survey conducted in four Canadian metropolitan areas in 2021, the results show that women and men in households with children exhibited different characteristics of grocery shopping across multiple dimensions. Women compared to men not only spent more time shopping, but also were less likely to drive to stores and more likely to shop during working hours and with companions. Gender differences were further compared among different classifications of grocery shopping patterns identified through latent class analysis. Various gender gaps were found across different classifications, with women shopping with others possibly having some of the most complex constraints. Multinominal logistic regression shows that shopping with others was associated with identifying as female, being relatively lower socioeconomic status, having greater housework responsibilities, and living in areas with higher grocery store density. Overall, this study provides evidence of nuanced gender gaps of grocery shopping in multiple dimensions, within different groups of people, and across a range of cities of various sizes. • Mobility dimensions are analyzed to examine gender gaps in grocery shopping. • Women differ from men regarding travel modes, shopping timing, and trip companions. • Various gender gaps are found across different grocery shopping types identified by LCA. • Women in the type “shopping with others” experience multiple constraints. • Urban environment is related to shopping types that exhibit more gender differences.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".