Conclusions and Recommendations

Conclusions and Recommendations

DOI: 10.4018/978-1-5225-7975-5.ch010

Abstract

But having said all that, we are not there yet, and 36 detailed recommendations follow. The authors believe there is something in these recommendations for many interest groups and individuals: feminists, gender theorists, and researchers; governments, policymakers, and taxpayers; parents, educators (primary, secondary, trade, and tertiary), the media and content developers; individual activists and advocates, traditional women in IT associations and their sponsors and supporters, and new social media-style women in tech associations and specialist groups; employers and recruiters; and above all, the individual women and men in technology. The recommendations are structured into logical groupings that work within the STEMcell model: hackathons and code camps, crowdsourcing and crowd funding, social media and join the conversation, and hangout and collaborate, all framed by the changing tectonic shift environment and with the overall goal to foster a curious, creative, and clever culture. The recommendations are also summarized in the Appendix.
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Yes! We are all individuals! – Monty Python’s Life of Brian

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Conclusions

For decades, we have been worried about how few women there are in IT and other technical fields. Based at least partly on the historical bias against women having any career at all, we have generated theories and interventions relating to surmised barriers that keep women out of IT or drive them from it after they enter it. We have achieved nothing.

But instead of questioning our assumptions, we have held them inviolable and linked them to increasingly subtle and insidious barriers. It gives the impression of women as a herd of frightened deer, ready to run at the mere sniff of a man.

Yet that is not how women in technology or girls interested in STEM see themselves: they see themselves as curious, competent and above all as people who regard obstacles as a challenge to be met and overcome.

That there are statistical differences between men and women is certainly considered controversial in some contexts. For example, when Google employee James Damore claimed that “the differences in the number of men and women in tech companies such as Google can be largely explained by biological differences, rather than sexism” (Ghose, 2017), this exploded virally and stirred furious debate, with the end result being that Damore was fired for perpetuating gender stereotypes.

But in fact statistical and biological differences are widely accepted implicitly or explicitly in less ‘hot-button’ contexts. Thus Cave (2013) noted, “It is widely acknowledged that women bring a different mix of skills to the workplace – the area of contention seems to be whether these differences are good or bad.” For example, “Both women and men believed that women affected the organizational culture in a positive manner: by encouraging more collaboration, more participative decision-making and hence more collegial workplaces” (Soe & Yakura, 2008). Similarly, “A wealth of research in the past decade shows that diversity improves problem-solving, productivity, innovation, and ultimately, the bottom line” (Ashcraft, Eger & Friend, 2012).

Ghose, (2017) provides a quote from Margaret McCarthy, a neuroscientist at the University of Maryland who studies gender differences in the brain: “It would be foolish to say there are no biological differences between men and women…we are biologically different. It would be crazy to say that difference in biology doesn’t to some degree extend to our brains. To think that we have somehow escaped millions of years of evolution because we are modern humans, I think, is just folly.”

Indeed, that there are relevant differences between men and women is implicit in many explanations in the literature for the shortfall of women – by the very fact that they affect girls specifically. For example, Ashcraft et al.’s (2012) argument that “Computing is often taught in the abstract... This lack of relevancy is troubling because making relevant connections is particularly important for increasing girls’ interest in computing courses and careers”, and Miliszewska and Moore’s (2011) conclusion that we need “an alternative approach – a re-conceptualization of ICT into an environment that women would naturally embrace.”

At school, it is considered that boys and girls have different learning styles and boys are more assertive in the classroom (Herrick, 2009), and “While boys and girls have very similar levels of academic ability, boys are substantially more likely than girls to choose more prestigious profiles” (Buser, Niederle, & Oosterbeek, 2012). It is interesting that this difference extends into adulthood: Cohen (2013) relates that generally women do not appear motivated by the prestige and self gratification of presentation, so when approaching female speakers TED adjust their requests to reflect the social impact of the presentation.

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