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Drange, Ida; Pietilä, Maria; Reisel, Liza; Silander, Charlotte – Studies in Higher Education, 2023
Which gender equality measures do Nordic universities use, and to what extent are the measures effective in increasing the share of women in top academic positions? Based on theories that distinguish between actor and structure-oriented measures, and between strategies of inclusion and transformation, we identified four types of measures: career…
Descriptors: Women Faculty, Females, Equal Opportunities (Jobs), College Faculty
Tiainen, Tarja; Berki, Eleni – Studies in Higher Education, 2019
Women's under-representation in the fields of science and technology is strong; both in software houses and academic posts. We focus on the academic field by gender sensitive analysis of Information and Communication Technology (ICT) academics. The general picture given by statistics' meta-analyses illustrates male dominance even in Finland, which…
Descriptors: Gender Bias, Science Education, Technology Education, Information Technology
Brunila, Kristiina; Ylöstalo, Hanna – Journal of Education and Work, 2015
This article deals with challenging the gender inequalities that exist in education and working life. It contemplates the kinds of discursive power relations that have led to gender equality work in Finland. In today's conditions where equality issues are being harnessed more strongly to serve the aims of economic efficiency and productivity, it…
Descriptors: Gender Bias, Equal Education, Equal Opportunities (Jobs), Power Structure
Mayer, Audrey L.; Tikka, Paivi M. – Journal of Higher Education Policy and Management, 2008
Several recent reports on the status of women in US academic institutions have recommended more generous family policies to encourage and retain more women among academic staffs. Many of the policies suggested are modelled on those that have been in effect in Nordic countries for decades. The status of women among Finnish and Swedish academic…
Descriptors: Sex Stereotypes, Females, Foreign Countries, Gender Bias