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Diversity and inclusion in the technology sector is increasingly debated, specially in the context of equal opportunities for all and a shortage of experts in many tech related industries. The need to be more inclusive can refer to different age groups, people with diverse culturally and linguistically backgrounds or gender. All in all, ethnic, gender and socio-economic diversity is not yet at the forefront of fabrication laboratories (FabLabs) agendas for change. This paper aims to contribute to the discussion of diversity and inclusion by primarily elaborating gender relations in FabLabs and, to a lesser extent, discussing age and socio-economic conditions of makers. Our analysis is based on 39 interviews and the analysis of 55,450 data points extracted from the log files of 3d-printers, CNC milling machines, laser cutters and cutting plotters. This combination of qualitative and quantitative data reveals that, indeed, some machines are used more frequently by men or women. However, the main difference is in absolute numbers, i.e. women are not joining FabLabs for a variety of reasons ranging from uninviting cultures to the lack of role models in technology driven areas in general.
ddc:300, 300
ddc:300, 300
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 16 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
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