Background Context

• Author: McNally, Sandra
• Pages: 14-18

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participation can be explain ed by measures of gender inequality (Section 4). However,

most of the gender gap is within country rather than between countries, and the

remaining sections focus on studies that hav e sought to expl ain the gender gap within

different count ries. I discuss the role of personal attributes: namely confidence, s elf-

efficacy and c ompetitiveness (Section 5) and the role of preferences and expectations

(Section 6). I go on to discuss features of the educational context thought to be

important for influencing attributes and preferences (or mediating their effects): peers;

teachers; role models; and curriculum (Section 7). I then briefly discuss broader cultural

influences (Section 8). Subsequently, I then use the literature reviewed to discuss policy

implications, also drawing on insights ma de by some of the authors of relevant studies

(Section 9) before concluding (Section 10).

2. Background Context

For tertiary-level education, gender segregation by field of study is very striking

and has been well documented in previous literature. For example, in their review paper

about women and STEM, Kahn and Ginther (2 018) di scuss this in relation to t he US.

They show that with re gard to STEM, female under -representation is limited to maths-

intensive science fiel ds – geosciences, engineering, maths/computer science and

physical science (which they call GEMP fields). They denote other ST EM fields as LPS –

life sciences, psychology and social sciences (excludin g economics). In 2014 in the US,

women received only 27 per cent of bachel ors’ degrees in mathematically intensive

GEMP fields but 69 per cent of bachelors’ degrees in LPS fields.

Figure 1 shows the percentage of women in tertiary education across a range of

countries. In the majority of countries shown here, there are more women than men in

tertiary education. However, Figure 2 shows a similar type of gender segregation in

broad STEM groupings across these countries (using Eurostat data). There are vastly

more men than women with degrees i n scienc e, techn ology, engin eering an d maths.

Having said that, the ra tio of men to women with degrees i n natural sciences, maths

and statistics is much more equal.

Statistics from UNESCO enable a slightly more detailed subject breakdown. They

are presented here for EU countries (for 2017) . Figure 3 shows the percentage of male

(female) graduat es by field as a percentage of male (female) graduates with tertiary

education. This is shown for each of the following fields: (A) engineering, manufacturing,

construction; (B) natural science, maths and statistics; (C) health and welfare; (D)

information and communication technologies. This shows a remarkable degree of

segregation across almost all countries, with (A) and (D) being more popular with men

and (C) being more popular with women. Only in natural science, maths and stati stics

are the proportions relatively equal – at least in many of the countries of the EU.

Although health and welfare may not always be included in some defi nitions of ST EM,

many programmes within this broad category require STEM skills.