Differences: Industries and Ethnicity

Differences: Industries and Ethnicity

DOI: 10.4018/978-1-4666-5860-8.ch009


Experiences in other industries and cultures are compared to put the issue of women in IT into a broader perspective in this chapter. The issues of low and declining participation of women are not unique to IT: similar patterns, theories, intervention programs, and results have been noted in other fields. However, in yet other fields women have risen naturally from a small minority to a substantial majority. This supports the thesis of this book that individual interest and choice are the main drivers of career choice. Among different countries and cultures, the proportion of women in IT varies from cases similar to ours, to cases where there is little difference between men and women. However, the latter represent different rather than less gender bias. It is argued that the power of #SocialIT to reach across cultural barriers directly to the individual and their personal interests will help women everywhere by showing them what is possible and giving them tools to achieve it themselves. The overall evidence is that interventions do not achieve their aims. To the extent that they have any positive effect, they do not increase numbers overall or benefit all minorities, merely rearrange the distribution. Not only have interventions had little positive effect, but the warning is made that we need to consider the unintended consequences of our well-meaning interventions.
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If your culture doesn’t like geeks, you are in real trouble – Bill Gates (Riddell, 2010)



Over my years of involvement in the issues of recruitment, promotion and attraction of women into technology fields, I have seen the perspective expand. Initially the interest was specifically in computing or more generally IT, then over time it became increasingly bundled with the related fields of Science and Engineering, which had been seeing similar issues. This occurred almost across the board in the literature, government policies and campaigns, gathering acronyms as it went: first with SET (Science, Engineering and Technology) and then STEM (Science, Technology, Engineering and Maths).

It is not surprising that we first see our own environment and then broaden our viewpoint to related fields experiencing similar issues. From the other side of that, we can learn from the experiences of people outside our own environment: both in other fields and other cultures. So in this chapter we compare issues of female involvement in industries other than IT and in non-Western or specific ethnic cultures.

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