Gender roles in technology adoption and usage

Gender, but also gender roles are often cited as one of the factors that could explain difference in adoption and uses for technologies. In a recent study the Pew Research Centre showed that in many countries men are still more likely than women to use the Internet (Pew Research Centre 2015). This is especially the case in Sub-Saharan Africans Nations. Nevertheless, the report also stated that significant differences in gender can be found in European countries such as France, the UK or Germany. Results are presented in Figure 3.1 in the original source document. Differences in terms of access were found for instance in a study by the World Wide Web Foundation, which found that only 20% of women from Nairobi's slums are connected to the internet compared to 57% of men (World Wide Web Foundation 2015). In many communities the lower access of women to technology is linked to their lower economic level and social status. They were also found to have, in average, a lower education level and thus fewer skills to use technologies (Wasserman & Richmond-Abbott 2005). Despite the differences in access, differences in skills and uses were also found in the literature review, but not all authors agreed on that topic (van Deursen & van Dijk 2011). Indeed, in a study about digital uses among seniors, Friemel found with a logistic regression that, if controlled for education, income, technical interest, pre-retirement computer use and marital status, differences in gender disappeared for duration of uses (Friemel 2014). Hilbert also proved that if women in Latin America and Africa have fewer access and use to ICT it is because of "their unfavourable conditions with respect to employment, education and income". He even found that at equal status, women turn out to be more active users than men (Hilbert 2011). Hargittai & Shafer (2006) found no significant difference in Internet skills between men and women but asserted that women self-assessed their skills in a significantly lower way than men which, again is rather related to gender roles than to gender itself. Similar results were found about Chinese and British students in a comparative study (Li & Kirkup 2007). But if the skills are not very different, at least in the richer countries where the technologies access rates are similar, men and women were still found to have different uses. For example, Schwartz et al found gender differences in the use of social media (Schwartz et al. 2013). They found for example that "females used more emotion words (e.g., 'excited'), and first-person singulars, and they mention more psychological and social processes (e.g., 'love you' and '<3' -a heart). Males used more swear words, object references (e.g., 'Xbox')". This corroborates Helen Nowicka's finding about women making use of social media in a way that is more about their own sociability than men, and thus do not use exactly the same social media, or use them differently (Nowicka 2014). Online and offline behaviours are tightly linked (Gille 2013; Denouël 2009; Back et al. 2010), thus technology use is sensible to interests and social practices, which are socially constructed and gendered influenced. For instance, women were found to share more pictures and videos online (Duggan 2013), or to use more apps to stop smoking (Kaur Ubhi et al. 2015), but these differences can also be found offline as their photography practices are different (Janning & Scalise 2015) and they have more incentive to stop smoking, especially related to pregnancy (Cahill & Perera 2015). Differences in uses have also been found within female population in rural communities in Kenya. Women's uses of technologies are not homogenous. Murphy & Priebe (2011) showed that mobile phones are used differently depending on the marital status, and the distance to the rest of the family for instance. Nevertheless, it became a tool of solidarity between women, as suggests the title of the article "My co-wife can borrow my mobile phone" (Murphy & Priebe 2011) as well as a way to be better be included in the society and to be linked to the urban communities.

Note: See source document for full reference.

Cultural Factors: Gender roles

Hazards: Natural hazards, Man-made non-intentional hazards or emergency situations, Man-made intentional hazards

Disaster Phases: Recovery, Response, Preparedness, Prevention, All disaster phases

Types of Actors Concerned: Non-active citizens