Is it all about early occupational expectations? How the gender gap in two science domains reproduces itself at subsequent stages of education: evidence from longitudinal PISA in Australia

ABSTRACT

Although the gender gap in non-compulsory science attracts much attention, few studies compare factors that shape it at subsequent life stages. Here, a life-course approach is used to examine the gender gap in science career expectations at ages 16, 23 and 26 for a recent student cohort. Then, a decomposition is applied to assess what share of the gender gap in Year 12 science, university science and post-university employment depends on earlier expectations to pursue a science career. The data, collected between 2006 and 2016, come from the population-representative Longitudinal Survey of Australian Youth, initiated with the Australian sample of the Program for International Student Assessment (PISA). Pathways into two science domains are contrasted. The first is biological and health sciences (BAH), the second entails computing, engineering, physics and mathematical sciences (CEM). The gender gap in occupational plans to work in science is widest in adolescence before stabilising in young adulthood. Yet, adolescence is also a life stage at which science is most popular as a potential career. Prior to university entry, up to one third of the gender gap in science can be attributed to individual motivation or characteristics. What can be explained, depends predominantly on occupational goals.

KEYWORDS:

• Longitudinal PISA
• science-related occupational expectations
• gender gap in science
• life-course perspective
• Australian youth

Disclosure statement

No potential conflict of interest was reported by the author.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Notes

1 Educational careers are understood here as sequences of events and transitions that make up an educational pathway of a young person. This is the pathway that leads to professional employment contingent on completing a specific stage of the educational pathway. Occupational careers are not always sequels to educational careers and can co-exist and complement each other.

2 It must be noted that the definition of BAH includes nursing, but if nursing, which is heavily feminized, is excluded, segregation patterns remain very similar.

3 Descriptive statistics for other variables are in Appendix 3.

4 These estimates are higher, particularly for males, than those in Figure 1, because Figure 1 is based on listwise deletion of missing data, i.e. students who did not answer this question were ignored.

5 Predicted probabilities reported for educational career outcomes are obtained using the margin command in Stata (Williams, 2012), from the model where gender is the only predictor. See (Adamuti-Trache & Sweet, 2014) for an illustration how predicted probabilities are used in science education research.