Page 86 - Through the gate of the neoliberal academy • Herschberg

84 CHAPTER 4
Data analysis
The research reports of the GARCIA teams were centred on recruitment and selection of early-career researchers including both postdocs and assistant professors. For this chapter we focused on the sections of the research report that involved the research findings on assistant professor positions. We applied thematic coding as a method for analysing our data (Flick, 2009). We first read the research reports on gender in recruitment and selection and open coded the texts. We produced short descriptions of each ‘case’ (national report) according to the themes in the reports (Flick, 2009): ‘context’, ‘power in the recruitment and selection of assistant professors in the STEM department’, ‘power in the recruitment and selection of assistant professors in the SSH department’, ‘gender in the recruitment and selection of assistant professors in the STEM department’, and ‘gender in the recruitment and selection of assistant professors in the SSH department’. This way, the central topics documented in the reports were summarized. Next, we compared the different ‘cases’, which revealed many similar recruitment and selection practices and gender practices (e.g., international mobility, gender stereotypes). We then deepened our analysis by applying selective coding through rereading all reports and looking for “further examples and evidence for relevant categories” (Flick, 2009, p. 312) regarding gender practices. At all times the cases (national reports) were compared. This resulted in a thematic structure of the gender practices found in the research reports. After multiple deliberations between the authors we ended up with two general gender practices, composed of six specific gender practices (see Table 4.2 for an overview). Selected passages of the research reports as well as interview quotes were analysed in greater detail. Repeatedly, we went back to the original research reports as well as the interview and focus group summaries to get additional information needed for our analysis. Our findings are illustrated with quotes from the interviews. The participant’s country (See Table 4.1 for country abbreviations), department (SSH or STEM) and sex (F for female and M for male) are provided. Quotes were translated into English by the respective research teams.
In the remaining part of the chapter we will use country names instead of the names of the participating institutions to facilitate reading. For example, when we refer to Switzerland, we refer to the participating institution in Switzerland. Also, we will use the terminology “SSH department” and “STEM department” when corresponding to the various departments in the six higher education institutions. See Table 4.1 for more information on the participating countries and the country abbreviations.