The social stratification of time use patterns

Abstract

Time use is both a cause of social inequality and a consequence of social inequality. However, how social class stratifies time use patterns is seldom studied. In this paper, I describe the time use patterns in the years 1983 and 2015 by social class, and gender in the British context. Using sequence analysis methods, I show how the diversity of time use patterns in British society is socially stratified. I find that 13 clusters capture the heterogeneity of time use patterns and that these clusters are associated with social class, gender, and day of the week. These clusters capture patterns of paid and unpaid work schedules, as well as leisure patterns. The results show that men have experienced a reduction of the standard Monday to Friday 8‐hr working day, while women have experienced a general increase in this type of schedule. On the other hand, patterns of domestic working days have reduced for women and increased for men. Important differences exist in paid and unpaid work patterns between social classes. Working‐class women have experienced an important increase in shift work on weekends. They are also much more likely to be doing unpaid work on weekdays compared to upper‐class and middle‐class women. Working‐class men are more likely to experience non‐working days and leisure days on both weekdays and weekends and are more likely to be doing shift work. They are also more often doing unpaid work on weekdays compared to men in upper‐class households. Patterns of childcare indicate that all families have increased their childcare time. Men in upper‐class households in particular have experienced an important growth in childcare time between 1983 and 2015. I conclude by discussing how time use can further our understanding of social stratification.

Contour of the Day: Social Patterning of Time in Later Life and Variation in Reported Well-Being in Activities

“…We apply sequence analysis techniques to the selected dataset in order to establish clusters of individuals with similar behaviors. These methods are appropriate to categorical data that consist of sequentially linked categorical states and our overall goal is to create a finite set of clusters made of homogenous sequences (Fasang and Liao, 2014;Vagni, 2020).…”

“…Although there are other techniques such as Latent Class Analysis that can be applied for the same purpose, there is not a clear superiority of one method and sequence analysis has been widely used in time use studies (Barban and Billari, 2012;Lesnard, 2010;Minnen et al 2016;Vagni and Cornwell, 2018;Vagni, 2020) We use TraMineR, which is an R package for mining and visualizing sequences of categorical data (Gabadinho et al 2011). To create the clusters, we identify and select the reported activity at minutes 0, 10, 20, 30, 40 and 50 of each hour 1 .…”

“…These methods are appropriate to categorical data that consist of sequentially linked categorical states and our overall goal is to create a finite set of clusters made of homogenous sequences (Fasang & Liao, 2014;Vagni, 2020). Although there are other techniques such as latent class analysis that can be applied for the same purposes, there is not a clear superiority of one method over another and sequence analysis has been widely used in time use studies (Barban & Billari, 2012;Lesnard, 2010;Minnen et al, 2016;Vagni & Cornwell, 2018;Vagni, 2020). We use TraMineR, which is an R package for mining and visualizing sequences of categorical data (Gabadinho et al, 2011).…”

“Women’s Work”: Welfare State Spending and the Gendered and Classed Dimensions of Unpaid Care

“…The class structure, too, has been shown to matter for the relationship between gender and unpaid care (Damaske 2020; England 2006). Overall, wealthier households perform less unpaid care work than poorer ones (Folbre 2012; Vagni 2020), likely due to a greater ability of the well-off to outsource this work to paid care providers—providers who are themselves likely to be immigrant and/or racialized low-income women (King-Dejardin 2019; Lightman 2020; Williams 2001). Yet the literature also finds that the gendered division of unpaid care is more equal within wealthier households (Ferrant, Pesando, and Nowacka 2014; Quadlin and Doan 2018; Sullivan 2000).…”

“…Yet the literature also finds that the gendered division of unpaid care is more equal within wealthier households (Ferrant, Pesando, and Nowacka 2014; Quadlin and Doan 2018; Sullivan 2000). Notably, however, this too is most often attributed to reduced hours of unpaid care work performed by higher income women, rather than to greater amounts of unpaid care work performed by higher income men (Gupta et al 2015; Vagni 2020).…”