Abstract
This chapter explores some key methodological applications using intersectional approaches to analyse risk. The point of departure is that multiple methods are needed to explore the different perspectives of risk and inequality. The chapter begins with a discussion of methodological implications of an intersectional approach in terms of fluidity and stability followed by an exploration of different methods divided by the structure—agency categorisation. The first category, which is not a category as much as dimensions of system-centred analysis, is exemplified with two studies that analyse two discourses, namely the Swedish policy for the Arctic and the media reporting of a Swedish wildfire in 2014. The second category, which represents different group-centred analyses, is illustrated by an analysis of how risk is done in everyday life. Thereafter, the possibility of applying quantitative methods whilst departing from intersectional risk theory is discussed and exemplified.
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Notes
- 1.
The risks that are included here are serious illnesses, such as cancer and heart disease, consuming alcohol, and pandemics such as Ebola.
- 2.
The safety measures included are having home insurance and a fire alarm.
- 3.
The dataset used in the analyses is composed of two representative samples of the Swedish population between the ages of 16 and 75: a random national sample of all inhabitants in Sweden (n = 2,500, response rate 41%) and a random sample of people living in three districts in Stockholm, Gothenburg and Malmö (n = 1,000, response rate 25%). In total, 1,078 people completed the questionnaire. The purpose of the second sample was to increase the number of people with foreign backgrounds in the dataset. Due to language problems and incomplete or inaccurate addresses, the response rate among people with foreign backgrounds was expected to be low.
- 4.
In Fig. 8.1 the different assemblages are illustrated using acronyms representing, in this order, gender (W for women, M for men), place of origin (A for Africa, South America, and Asia; E for Europe) and social class, measured by income (LI for low income, MI for middle income, and HI for high income). Altogether 18 assemblages were created this way: WALI, WAMI, WAHI, MALI, MAMI, MAHI, WELI, WEMI, WEHI, MELI, MEMI, MEHI, WSLI, WSMI, WSHI, MSLI, MSMI, MSHI. For a more detailed description of how to use and interpret Multiple Correspondence Analysis, see Öhman and Olofsson 2019).
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Giritli Nygren, K., Olofsson, A., Öhman, S. (2020). Methodological Applications. In: A Framework of Intersectional Risk Theory in the Age of Ambivalence. Critical Studies in Risk and Uncertainty. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-33524-3_8
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