Nordwit recently had its two-day Spring meeting, through zoom of course. One of our topics was statistics and particularly statistics on gender and gender (in)equality in research and innovation.
We all agreed that we like – or even love – statistics. The academic world is full of statistics that we produce and use in many ways. The world outside the academy – politicians, media, experts in public and private sector organizations – eagerly wants to have statistics to be able to name facts. Statistics and numbers are found equivalent to factual knowledge social phenomena including gender inequalities. Thus, the statistical figures represent an image of a hard and true knowledge. People rely on facts, and the possibility to present numerical facts provides convincing truths. However, during our discussion it also appeared that statistics are far from easy to find, and even more difficult to interpret in the analysis of gender inequalities.
Statistics around gender inequalities are produced both in national institutions such as Statistics Finland, ministries, labor unions, Technology Industries of Finland, and supranational institutions such as OECD, ILO and European Commission. The numbers presented in the statistics derive from various sources. These sources also include a variety of definitions and guidelines according to which the raw data is classified. My close colleague Merja Kinnunen (1997) analysed already twenty years ago how gender was embedded in statistical classifications in Finland. She showed that classifications are institutionalized texts, which are also a means to manage and control the material world. The classifications include cultural perceptions, symbols and images and at the same time they describe structural features of society. Thus it is worth remembering that the statistical descriptions also shape, maintain and legitimate the existing structures.
Currently supranational statistics such as She Figures, a key source for an analysis of gender questions, are based on other supranational databases such as Eurostat. However, the assumption is that these originally national sources, are equivalent and they measure the same issues in each society. This has needed a lot of standardization and negotiation. It has been necessary because equivalent information provides better chances to make comparisons between the countries. Still, it is relevant also to ask the same questions that Merja Kinnunen (2001) posed: How do the classifications and statistics as institutional texts participate in the legitimization of the differences and hierarchies between women and men in society? As statistics is highly standardized across the (Western) countries, it is also relevant to ask, what kind of reality do the standardized numbers tell and what kind of reality remains hidden behind the figures?
Päivi Korvajärvi
Sources:
Kinnunen, Merja (1997) “Making Gender with Classifications.” In: Rantalaiho, Liisa & Heiskanen, Tuula (eds) Gendered Practices in Working Life. London: Macmillan, 37-51.
Kinnunen, Merja (2001) Luokiteltu sukupuoli [Classified Gender]. Tampere: Vastapaino.
She Figures 2018 (2019) European Commission, Directorate-General for Research and Innovation. Luxembourg: Publication Office of the European Union.
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