When gendering meets ageing: intersections between ICTs-related sexism and ageism in Italy

The impact of digital technology in people’s life is interdependent with social inequalities based on gender, age and other differential factors. Stereotypes reinforce such inequalities, including digital ones that relegate women and the elderly to the margins of network society. Studies on both ICTs-related sexism (Sáinz & Eccles 2012; Comunello et al. 2017, among others) and ageism (Fleming et al., 2018; Comunello et al., 2020, among others) have already shown that digital technology is commonly perceived as a young and men-dominated field. Incipient research on the intersection between gender and age in the specific ICTs domain has proved that it influences how people perceive their own and other’s digital media usages (Harvey, 2015; Oudshoorn et al., 2016; Panarese & Azzarita 2020, among others). Driven by literature about both gender and digital technology (MacKenzie & Wajcman 1999; Van Oost 2003; Van Zoonen 2002; Ganito, 2010 among others), and generations and digital technology (Blaschke et al., 2009; Domínguez-Rué & Nierling, 2016; Neves, & Vetere, 2019; Peine & Neven, 2020 among others), our study provides a deeper understanding on how ICTs-related sexist and ageist (self-)stereotypes intersect with each other. We carried out 6 online focus groups with Italian male and female participants from two different age cohorts (20-30 and 65-75 years old, respectively). We conducted one women-only, one male-only and one mixed-gender focus group per age group to capture both complicity and contrasting interactions between genders. Initially, we simulated a game. Participants had to guess the age and gender of some fictional characters we sketched out based on ICTs usages. This stimulus triggered both identification and differentiation processes among participants, who identified or distinguished themselves and close contacts from some of the characters. In this process, they selected only a few of the mentioned ICTs usages as representative of (allegedly) typically female vs male, and youthful vs old usages, thus “gendering” and “ageing” the ICTs usages based on related sexist and ageist stereotypes. Then, we stimulated a collective discussion about official data concerning gender differences in ICTs uses, skills and preferences. Participants resorted to sexist stereotypes to explain data related to gender inequalities, without neglecting the weight that generational belonging might play in such phenomena. At this intersection they often opine about who does what and how, thus “gendering” and “ageing” the users based on ICTs-related sexist and ageist stereotypes. Only few participants acknowledged the role of cultural conditioning underlying the gender and age inequalities that the data summarized. In doing so, they mapped out the origin of the stereotypes they themselves drew upon for their responses. Finally, we sketched out ICTs-related everyday situations in which participants had to choose who to turn to and argue why. In this case, stereotypes emerged in more nuanced ways, if at all. Catapulted into their daily dynamics, participants offered a more multifaceted picture of what women and men, young and old people, do with ICTs. They downplayed those processes of “gendering” and “ageing” that previous abstract stimuli solicited.